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December 14, 2019, 10:26:21 am

Author Topic: University of Melbourne - Subject Reviews & Ratings  (Read 1077123 times)  Share 

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Paulrus

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Re: University of Melbourne - Subject Reviews & Ratings
« Reply #630 on: December 22, 2016, 06:25:56 pm »
+5
Subject Code/Name: PSYC20006 - Biological Psychology

Workload:  2 x 1 hour lectures per week, and 1 x 2 hour tutorial every second week

Assessment: 2000 word lab report split into two evenly weighted sections (each 1000 words and each worth 20%), due in weeks 5 and 9 (40%), 2 hour exam consisting of 120 MCQ (60%)

Lectopia Enabled:  Yes, with screen capture.

Past exams available: No, but practice questions are on the LMS.

Textbook Recommendation: Physiology of Behaviour is the prescribed textbook, but you'll never need it so it's not worth buying. If you really decide you want a copy, it's fairly easy to find a pdf.

Lecturer(s):
Piers Howe - Brain Imaging Techniques (3 weeks) and Statistics (1 week)
Amy Jordan - Sleep and Emotions (2 weeks)
Jacqueline Anderson - Neurobiology of Memory (2 weeks)
Olivia Carter - Psychopharmacology (4 weeks)

Year & Semester of completion: Semester 1, 2016

Rating: 4.5 out of 5

Your Mark/Grade: H1

Comments:
The course and staff have changed a fair bit since the other reviews for this subject were posted, so I figured I'd try give a more recent perspective on it. Content-wise, this is my favourite subject I've done in undergrad so far. There are a few small things that brought down my mark a tiny bit, but overall it's a fantastic subject that I wholly recommend doing.

Lectures:
Piers does a great job of teaching brain imaging techniques, a topic which could easily be fairly dry. Instead, his lecturing style is actively engaging and I actually found his lectures pretty interesting. He covers transcranial magnetic stimulation (TMS), electroencephalography (EEG), and functional magnetic resonance imaging (FMRI), as well as t-tests in the statistics component. His lectures are extremely content heavy (expect 100+ slides per lecture) and you're expected to know things in a good amount of detail, but understanding is more important than rote-learning. His section can get a bit complicated if you're not particularly scientifically inclined (particularly in that you're expected to understand the physics underlying the different imaging techniques), but it is biological psych after all so that's to be expected.

Amy covers sleep and emotions - more specifically, the biology and structure of sleep, sleep disorders, and the physiology of emotions. Her section is mostly straightforward and there's not a particularly large amount of content, which is nice. She's a really great lecturer (and also a lovely person) and her content is both absorbing and applicable to everyday stuff, which makes her section super enjoyable.

Jacqueline's section on memory is kinda disappointing - a lot of the stuff in her lectures is actually really interesting, but the way she teaches is extremely dull and sounded a bit like a synthesised text-to-speech generator. Her slides were also bland as fuck and had a lot of blurry diagrams filled with extraneous details, which made it hard to know what you needed to know. Despite that, her section is solid if you focus on the content itself, but it's a bit disappointing knowing that it could have been a lot better.

Olivia teaches psychopharmacology and she is FANTASTIC. She's an extremely engaging lecturer and her part of the course is fascinating. She's probably my favourite lecturer I've ever had at university. She generally focuses on a particular hormone/neurotransmitter (or group of them) within a given lecture and discusses their action on the body and nervous systems in detail, as well as their synthesis/breakdown and chemical composition, along with pharmaceutical and experimental applications (e.g. one week focuses on acetylcholine in relation to attention and memory). She also taught us that Calvin Klein (or CK) is a street name for mixing cocaine and ketamine, which is definitely the most applicable thing I've learned at uni so far.

Tutorials:
My gripe in this area is one that's common to the majority of psych subjects: once you finish the lab report, the tutorials are mostly useless. They're invaluable for the lab report, and you'll do all of your SPSS data analysis in the tutorials (which you'll interpret and write up at home). After that, the tutorials are kinda useless and mostly consist of filling time. Some of the stuff was interesting, like running and designing an experiment on caffeine and cognitive performance in the last two tutes - but again, it wasn't examinable, so it just felt like a bit of a time filler.

Assessment:
The topic for the lab report might change depending on the year (not sure), but we looked at the different brain areas involved in spatially-primed and unprimed visual search tasks. For the first part, you're expected to write the introduction and methods sections - for the second, you revise your intro and methods based off tutor feedback, as well as writing up your results, discussion and abstract. We were taught in the tutorials how to write up the lab report in a general sense, but you were kinda left in the dark about exactly what you should include and the instructions were a bit vague. It would have been difficult to do well on the assignment without consulting the coordinators' posts on the discussion board (to their credit, the coordinators did a good job of answering questions). Writing in APA format for lab reports (which is much, much more difficult and anal than writing essays in APA) was also not taught, but was assumed knowledge, which is a bit unfair as this would have been the first proper lab report many students would have written. However, these criticisms were pretty much true of every psych subject in second year, so I think the psych department just expects you to take initiative and work things out for yourself (for better or for worse).

The exam was pretty chill and mostly fair. Amy and Jacqueline's sections were both relatively easy and I think they recycled a small number of questions from the online practice questions. Olivia's section was a bit more challenging, but not as difficult as it could have been given the amount of detail in her lectures. All of her questions were fair and didn't assess anything that was outside of the course, so if you revised well then you should have been fine. Piers's questions were definitely the hardest and a lot of people struggled with them. They featured a few (emphasis on few) slightly dodgy questions where it was a bit unclear what was being asked, and where you could have realistically picked two different answers depending on how you interpreted the question, which is a bit disappointing. For statistics, there's much more of an emphasis on the underlying theory than there is on being able to do calculations, so make sure you know HOW the calculations and formulas work rather than just being able to plug them into a calculator. Overall though, it was a pretty fair exam.

Overall:
Fuck, this is longer than I expected. TL;DR - Super interesting subject with a mostly really great teaching staff, brought down very slightly by small factors, but still would very much recommend.
2015-2017: Bachelor of Arts (Psychology) at University of Melbourne.

stolenclay

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Re: University of Melbourne - Subject Reviews & Ratings
« Reply #631 on: January 17, 2017, 03:57:52 am »
+7
Subject code/name: MAST20022 Group Theory and Linear Algebra

Workload: Weekly: 3 x 1-hour lectures, 1 x 1-hour tutorial

Assessment:
3 individual assignments20%
3-hour end-of-semester exam80%

Lectopia enabled: Yes, with screen capture, but the document camera may not be used; please see below for more comments.

Past exams available: In 2016 Semester 2, two past exams were available with solutions. More were available on the library website without solutions.

Textbook recommendation: No external texts required. A very comprehensive set of lecture notes is provided and is certainly sufficient.

Lecturer(s): Dr Alexandru (Alex) Ghitza

Year and semester of completion: 2016 Semester 2

Rating: 5 out of 5 (tempted to deduct something for that fire alarm evacuation... HAHA)

Comments:

Just what is group theory? Why am I learning linear algebra again? And why is it that every time I tell someone about this subject they think I'm talking about two subjects?

MAST20022 Group Theory and Linear Algebra is a second-year subject that is a prerequisite for third-year pure maths subjects. Pure maths, being the obscure field it is, is certainly no less obscure as a maths specialisation, which is probably why your general audience always assumes you are talking about two subjects.

Group theory is the study of a mathematical construct called groups (surprise surprise). Groups are best motivated by the observation that in mathematics, there are many types of sets that, when endowed with a certain operation (a rule of combining two elements in the set), satisfy some common properties, namely
  • associativity: (\(a \cdot (b \cdot c) = (a \cdot b) \cdot c\); tersely, your order of evaluation is irrelevant);
  • identity: there is a "do nothing" element; and
  • invertibility: every element has an element that "undoes" it.
A common example would be the integers \(\mathbf{Z}\) under addition: addition is associative, permits an identity element (namely \(0\)), and naturally gives rise to an inverse for every integer (just negate the integer). Such properties seem like fairly simple properties to come about, and, indeed, in GTLA you will come across a variety of groups.

Group theory forms a natural foundation for the field of abstract algebra, which, loosely, is the study of the structure of sets in mathematics. In this sense, GTLA opens students to further studies in algebra at the university. Unfortunately, aside from MAST30005 Algebra, these subjects are taught at the graduate level. The field of algebra enjoys the reputation of being a rather beautiful field of mathematics, and this same sentiment manifests in the university environment: MAST30005 Algebra is widely reputed to be one of the most enjoyable undergraduate maths subjects. Personally I believe its beauty lies in the fact that groups are introduced with only the simple properties mentioned above, but as more structure (read: conditions and properties) is imposed on the groups, the results become increasingly rich and eye-opening (at least that happens to be my take on GTLA). If ever there was anything I would call "mathemagic", this would be it.

So far I have yet to mention linear algebra. Why exactly is this subject a combination of both group theory and linear algebra, and where is the relationship between them? The group theory and linear algebra topics in GTLA happen to be fairly disjoint; one could outright label each topic as either "group theory" or "linear algebra" without hesitation. However, there are a few parallels between the structures of vector spaces and groups, the most obvious of which is that a vector space over a field satisfies all the aforementioned properties of being a group! As you will see, there are more parallels (bases and generating sets, (normal) subgroups and linear subspaces, homomorphisms and linear transformations); some of these are mentioned, so rest assured that, despite the abstract nature of the group theory topics, many phenomena you have in fact encountered in earlier linear algebra studies. The only other connection that was obvious to me was that some of the groups we worked with directly involved matrices and their properties.

Being a pure maths subject, you might expect the content in GTLA (particularly the group theory topics) to be quite separated from "real world" applications. To an extent this is true; however, Alex does present some highly intriguing applications of both group theory and linear algebra, such as in computer cryptography, special relativity, chemistry (brief mention), and even stochastic processes! Some of these have entire lectures dedicated to them (but are not examinable), in case a passing mention of applicability is not convincing enough.

I would say that students studying GTLA tended to be maths students (no surprise here) but also physics students who might be considering further studies in quantum physics. Quantum physics, to my knowledge, relies on the theory of metric spaces and Hilbert spaces (cue MAST30026 Metric and Hilbert Spaces, although it is not a prerequisite for the university subjects on quantum physics), which, in turn, relies on some of the content in GTLA.

The difficulty of GTLA lies in its breadth of content. The lectures are very proof-based, and there are many smaller results and properties presented aside from the main ones, some of which you will need to recall very quickly and use frequently. It is a style of mathematics rarely found outside pure maths and is understandably a struggle for students for which GTLA is a first exposure to pure maths beyond first-year linear algebra and real analysis. Alex takes a very structured approach to this subject (teaching theory and then giving many examples), and consequently it was far easier learning this subject than one might expect from its content.

Subject content
There are five major areas of discussion in the subject, and they are conveniently allocated (usually) one question in Part B of the examination (more on that later). These are:
  • the Jordan normal form;
  • an introductory discussion on groups with a slight focus on normal subgroups;
  • inner product spaces;
  • group actions; and
  • the Sylow theorems (or, more generally, classifying groups).

Introductory topics
Alex begins with a short illustration on what sorts of problems motivate the study of abstract algebra. From this short lecture alone it was quite easy to see that this subject was going to be different from first-year maths subjects. With uses in studying symmetry, geometric properties, and number systems, the main theme was that abstract algebra is quite literally the abstraction of ideas that are present in various mathematical objects.

The first point of call (even before the Jordan normal form) is the discussion of the principle of mathematical induction (which should be familiar from MAST10008 Accelerated Mathematics 1) and something called the well-ordering property, which states that a non-empty subset of the natural numbers \(\mathbf{N}\) always has a smallest element. The principle of mathematical induction and the well-ordering property are shown in lectures to be equivalent.

At a glance it is probably unclear why the well-ordering property is important or even why it is a result on its own (it sounds "obvious"). Perhaps this is more an example of the fragility of mathematical logic: In AM1 you may have used the principle of mathematical induction several times without questioning its validity. It turns out that when setting up the theoretical environment for studying mathematics, either the principle of mathematical induction or the well-ordering property needs to be introduced as an axiom, that is, something accepted as true without proof. Once this is done, the other is immediately true due to their equivalence, and you can use them to your heart's desire.

This delicate and rigorous approach to logic is somewhat characteristic of studies in pure mathematics, and at various points throughout GTLA and further pure maths studies, you will probably come across proofs for things which you deemed intuitive or obvious.

Following this is some basic number theory and definitions of some types of groups. Number theory is the theory surrounding integers and investigates aspects such as divisibility or factorisation. Admittedly it is not a very prominent topic in GTLA; the areas discussed are the Euclidean algorithm (arising from the division algorithm), Bezout's identity, some properties regarding divisibility, some modular arithmetic, and the fundamental theorem of arithmetic. The results here are discussed in the context of the integers, but some generalise (to an extent) to other sets, such as the set of polynomials. In fact, you will encounter Bezout's identity applied to polynomials later on.

The \(\mathbf{Z}/n\mathbf{Z}\) class of groups is carefully defined during the discussion of modular arithmetic (even though you have not been told what a group is). This class of groups reappears frequently in GTLA and is probably the type of group with which you will become most familiar.

Following the number theory topics, some types of groups are defined. Starting with the most general, these are:
  • rings,
  • commutative rings,
  • fields, and
  • algebraically closed fields.
All algebraically closed fields are fields, and all fields are commutative rings, and so on. The purpose of this short section is to define fields and algebraically closed fields, which is necessary to understand the next topic on the Jordan normal form, as they are mentioned in some definitions and results.

Properties specific to these types of groups are not really discussed in GTLA, but it is important to know what the definitions of these types of groups are. Admittedly it might be easier to revisit these definitions once you are taught the definition of a group (which is yet to take place at this point).

The Jordan normal form
The first major topic, the Jordan normal form, essentially occupies the lectures in Weeks 3 to 6. The main result can be stated quite easily, but there is a myriad of intermediate results leading up to it. In fact, you do not even discuss all the intermediate results completely (an important one is left for MAST30005 Algebra).

The motivation behind studying the Jordan normal form is that many square matrices, when interpreted as linear transformations, are actually the "same" linear transformation but expressed with respect to a different basis. Equivalently, a linear transformation interpreted for different bases gives you many different matrix representations, but they are fundamentally really one and the same. Imagine, in \(\mathbf{R}^3\)
  • a dilation by a factor of 2 from the \(x\)–\(y\) plane; and
  • a dilation by a factor of 2 from the \(y\)–\(z\) plane.
These are really quite similar — they are the same linear transformation but for different bases.

The Jordan normal form of a matrix is the simplest square matrix among all those which can be said to be the same linear transformation as the original (the basis will generally be different). Notably, the Jordan normal form is unique up to permutation of the basis vectors, and its simplicity comes in the form of being almost diagonal.

This topic comes under linear algebra, and you will need to be familiar with first-year linear algebra content to understand this topic, as there is very little time for revision, and new ideas are introduced fairly quickly. Make sure you know what these are: subspaces, spans, bases, row reduction, the rank–nullity theorem, linear transformations, change of basis, eigenvalues, and eigenvectors. Alex includes thorough notes for these first-year topics, but they are hardly discussed in lectures.

The number of intermediate results for this topic is quite remarkable, and it will probably be overwhelming to be familiar with all of them. I would recommend being familiar with properties of invariant subspaces (subspaces which are invariant under a linear transformation), as they are most easily examined; there are quite a few tricks involved with the other intermediate results.

Overall this topic is a very involved and instructive exposure to the Jordan normal form; there are numerous defined stages, and the way it is delivered certainly feels like you are stepping through history (the stages are something like: square matrices \(\to\) block diagonal matrices \(\to\) upper triangular block diagonal matrices \(\to\) almost diagonal matrices i.e. the Jordan normal form).

The topic concludes with lectures discussing applications of these results to special relativity and Markov chains.

Introduction to groups
After 6 weeks of lectures, you are finally properly introduced to the foreign half of the namesake of this subject. Several definitions and properties are immediately thrown at you; as a completely new mathematical object, it is bound to be overwhelming at the offset.

My recommendation is to study these new definitions, properties, and concepts in the context of a single group. This is done in many examples in lectures, but if you find this to be insufficient in consolidating these concepts, then isolating a single group (maybe a dihedral group or \(\mathbf{Z}/n\mathbf{Z}\)) and studying all the discussed concepts (subgroups, orders, finding generators, finding homomorphisms to other groups, normal subgroups, applying the first isomorphism theorem, and so on) in the context of that group may help.

In becoming familiar with these concepts, I also found it invaluable linking group concepts with those in vector spaces. There are some very obvious parallels, and your greater familiarity with vector spaces may mean that drawing parallels allows you to grasp the group concepts more quickly.

There are several classes of groups appearing frequently throughout GTLA. You definitely need to know what these are by their symbolic representations, as they may not be defined in the questions that use them. These include
  • \(\mathbf{Z}/n\mathbf{Z}\) for natural \(n\) under addition (for \(n > 1\) but especially prime \(n\));
  • the dihedral group \(D_n\) consisting of symmetries of a regular \(n\)-gon for \(n > 2\);
  • the symmetric group \(S_n\) consisting of permutations of \(n\) distinct elements;
  • the general linear group \(\mathrm{GL}_n(K)\) consisting of invertible \(n \times n\) matrices with entries in a field \(K\) (with the operation being matrix multiplication); and
  • the special linear group \(\mathrm{SL}_n(K)\) consisting of \(n \times n\) matrices with determinant \(1\) with entries in a field \(K\) (with the operation being matrix multiplication).

With algebra being the study of structures of sets, some concepts are introduced in this topic to study the structure of groups. The existence of a homomorphism between two groups means that their structures are similar (in the way that elements interact with each other). The existence of an isomorphism between two groups means that their structures are identical.

The main result in this topic is the first isomorphism theorem, which gives a decomposition of a group's structure if there is a homomorphism with another group. For example, the non-zero complex numbers under multiplication is a group, and, using the first isomorphism theorem, one part of its structure can be identified as the structure of the positive real numbers under multiplication.

Another notion related to the decomposition of group structure is a normal subgroup. Together with the first isomorphism theorem (in which normal subgroups make an appearance anyway), they make up the majority of the methods used to study group structure in GTLA.

One of the other important sections in this topic is the theory on free groups. A free group is a type of group where elements have minimal properties (this is not a rigorous description). By imposing properties on certain elements, a free group assumes more structure. Free groups are introduced to discuss group presentations, which, given a particular group structure, are the ways of changing the structure of a free group to arrive at that particular group structure.

Group presentations are thus bare representations of group structure. They are not used heavily in GTLA, but it is good to know that there is a universal notation for talking about group structures. Sometimes Alex may use a group presentation to denote a group [structure] instead of using its common name, mostly for dihedral groups (the group presentations have the potential to be horrendous). There is also a small section on using group presentations to study homomorphisms between groups.

At the end of this topic is a short example relating group theory to RSA cryptography.

Inner product spaces
After a decent exposure to group theory is a topic on inner product spaces, beginning at around Week 10.

Inner products are no stranger: you have encountered its definition in AM1.

An inner product space is simply a vector space endowed with an inner product. With an inner product, notions like distance, length, orthogonality, and angle come into existence. This topic is (probably) the most important in preparing for future studies in topology (MAST30026 Metric and Hilbert Spaces).

While inner products were largely studied in the context of real numbers in AM1, the treatment in GTLA is more general. This is important if you remember a part of the definition of an inner product as symmetry — this is not true outside the real numbers.

The Gram–Schmidt process makes a reappearance with the appropriate reassurance that it is indeed an algorithm for finite-dimensional inner product spaces.

The most important concept introduced is the adjoint of a linear transformation on an inner product space. Its inclusion seems somewhat arbitrary at first but is necessary in discussing the intermediate results leading up to the major result of this topic. Linear transformations can be classified as certain types if conditions involving itself and its adjoint are satisfied. The different ways of characterising these types of linear transformations is the focus of a few of the results in lectures and problems in the tutorials and exams — sometimes you will be asked to prove that two different characterisations are equivalent. This can be quite difficult because of the numerous characterisations (I certainly do not recommend memorising the proofs), but luckily in exam situations hints are given.

The spectral theorem, the main result of this topic, states the conditions under which matrices can be represented as a diagonal matrix with respect to an orthonormal basis. You may recall in AM1 that this was always possible for real symmetric matrices; that was no coincidence, and the spectral theorem is the more general result.

Group actions
This is a short topic which begins in the middle of Week 11.

A group action is a set of rules dictating how a group interacts with a general set. The set may even be a group itself, which makes for slightly richer results.

There is a bit of terminology to learn, particularly when discussing the conjugation group action (this is a type of group action on a group).

The main result here is the orbit–stabiliser formula, which relates the number of elements in the group involved in a group action to other characteristics of the group action. These characteristics of the group action happen to be relatively easy to determine (at least that is the case in GTLA), so the result is useful when the group is not completely known.

Sylow theorems
This topic is even shorter than the topic on group actions is and only takes one or two lectures — in fact, it is included under the group actions section in the notes, even though the results themselves do not involve group actions. They are, however, a generalisation of Cauchy's theorem, the proof of which relies on group actions.

The Sylow (pronounced sill-low) theorems are results that assert the existence of subgroups of certain sizes in a group. More precisely, there are four results, and you will have to memorise these results, because their proofs are not discussed in GTLA (I gather they are probably far too difficult).

These theorems are the last major tool used to study the structure of groups in GTLA, and the relevant problems in the exam are usually also the harder ones.

The subject ends on a brief note of the massive mathematical work dedicated to classifying group structure. From 1955 to 2004, mathematicians collaborated to classify all finite simple groupsfinite referring to the number of elements in the group and simple referring to the fact that the structure is monolithic and cannot be decomposed further. It was a work that required tens of thousands of pages and is just further proof that group theory, though founded on a novel three-part definition of a group, is certainly no simple matter.

Lectures
Alex produces a ridiculously comprehensive set of lectures notes, on which the lectures are based completely. These are incrementally provided on the subject's website at http://www.ms.unimelb.edu.au/[email protected]/teaching/gtla/ (Alex really only used the LMS for some announcement emails). The set of notes is beautifully produced in \(\LaTeX{}\), with numbering and labelling of basically everything (such as Theorem 4.43, Lemma 3.22, or Example 4.9). The notes are even labelled with the dates on which content was discussed in lectures and some estimates of when future content will be covered.

That is not to say that lectures are unnecessary, but it is certainly a relief that basically everything discussed in lectures is written in mathematical prose.

The lectures themselves are of a high quality, and Alex consistently gives clear concise explanations for new concepts. Being an abstract subject, it was brilliant to see so many examples for everything. After introducing new concepts (or sometimes before the introduction, in order to clarify the motivation for studying them), Alex would discuss concrete examples and explain how parts of the definitions were satisfied, how the properties hold, how to apply an algorithm to this case, and so on. It was helpful to see all the theory in action in a lecture, and this made the subject far less intimidating.

Even putting aside the fantastic lecture quality, I would recommend going to lectures simply because Alex makes most of his announcements there. Unless you are stringent in regularly checking the subject website (or watching lecture recordings), it is possible you may be late in finding out important information. Sometimes tutorials also required content from the current week (more on that later), which means even lecture recordings are not timely enough.

Alex does not ask the students many questions during lectures, but keep in mind there is consistently quite a lot of material that needs to be covered, so opportunities for open brainstorming by students are few and far between.

On the note of the amount of content, I would say that in 2016 Semester 2 lectures were slightly behind, given that there was sometimes a bit of rushing at the end of lectures. All content was covered by the end, however.

Alex writes on the whiteboard during lectures, so it is ideal not to sit too far back. Technically both video (for the document camera) and audio are recorded, but the video is inherently not of much use. In 2016 Semester 2, Alex used the document camera for one of the lecturing venues because the students were seated too far from the whiteboard for it to be useful. I assume that this means the whiteboard will always be used unless it is physically infeasible during lectures.

Tutorials
Tutorials follow the traditional format for maths subjects. You are given a tutorial sheet at the start of the tutorial and form groups to solve the problems.

I would say that tutorial problems were generally hard, but this needs qualification: because of the new concepts and definitions that were consistently being introduced in lectures each week, unless you were consistently up to date with a good memory of all the definitions and results, you would not even be able to attempt the more basic problems on the tutorial sheets.

Realistically speaking, there were only ever one or two problems (out of seven or eight) that required innovative ideas or tricks; tutorial problems were by and large computational or simple applications of definitions or results. Sometimes a technique that was used in a proof in lectures would come in use, so it is important not only to know the content delivered in lectures, but also some of the methods and tricks employed in some of the delivered proofs, which Alex may not always explicitly point out. For example, if you are given that an inner product of certain elements in a vector space is always 0, then attempting to make both operands the same expression would mean that the operand has to equal 0 by the definition of an inner product. This is a technique used a few times in the inner product spaces topic.

Tutorial sheets are made available online on the subject's website, and at the end of the week solutions are also made available. The solutions contain fairly comprehensive working, so you should be able to understand solutions to all tutorial problems by the end of the semester.

I am not sure if this was intentional, but sometimes tutorial problems involved content which had only been delivered in lectures occurring in the same week as the tutorial. Older students will know that problem-based tutorials usually only have problems that need content covered up until the end of the previous week. I took this as a further sign that lectures were behind schedule, but even though my own tutorial was in the middle of the week, I never encountered problems in tutorials that needed content that was yet to be covered, so it is possible that the tutorials were deliberately scheduled to make this possible.

Assignments
There are three assignments throughout the semester, all uploaded on the subject's website (not the LMS). These are collectively worth 20% of your final grade; precise information about the breakdown was not provided.

Make sure you know when they are released, because assignment releases were not announced on the LMS; Alex points out in lectures when they are released, although this was sometimes one or two days after it was already available on the website (in case you are very keen).

Assignments are released before the required content has been fully covered, but it is still possible to complete some of it at the time of release. Students are given slightly more than two weeks to submit for each assignment.

Assignments are not very difficult and are fairly short; the difficulty is comparable to those on tutorial sheets, and most assignment problems are also direct computations or simple applications of results. In 2016, there was one question which introduced a new concept, but it was not mentioned again elsewhere.

Be careful to give full justification for everything; rigour is absolutely vital in pure maths.

End-of-semester exam
The exam is 3 hours long and is divided into Parts A and B. As with many maths subjects, it constitutes 80% of your final grade in GTLA. Historically, the exams that Alex has prepared have all been worth 100 marks each, with Parts A and B each worth 50 marks.

Part A is an act of mercy, honestly (given the difficulty of this subject): it consists purely of tutorial questions, many of which are reproduced verbatim, others of which may involve different numbers but otherwise can be dispensed with identically. This is announced by Alex to be the case, so this is not secret information or anything.

The message here is clearly that you should practise and be able to provide solutions to every single tutorial problem. This is not very far from knowing all the definitions and results fairly competently, but as mentioned earlier the more technique-based problems will require more attention. I am not recommending that you memorise solutions to all the tutorial problems; I am, however, advocating in favour of a good knowledge of all the definitions and results (no surprise here) and a reasonable familiarity with the techniques used in some of the harder tutorial problems.

Part A contributes a maximum of 40 to your final grade, so with a reasonable assignment performance, passing GTLA should not be an issue, even if you insist on rote-learning solutions to tutorial problems. Note that this is not a hurdle exam.

Part B is the more involved section of the paper, with a multi-part question dedicated to each of the topics outlined in the subject content above. Group actions and Sylow theorems are treated as one topic, so it is possible that one may not be tested in Part B.

The questions in this section are overall substantially harder than all tutorial problems (even the harder tutorial problems). The difficulty is mitigated in that marks are split between more parts, many of which are clues towards what may be useful in later parts. Sometimes hints are also explicitly included for harder questions.

There is nothing in Part B which requires the reproduction of a proof given in lectures, so there is no need to memorise those proofs. You may be required to prove a simpler version of results in lectures, however. For example, if a proof of the equivalence of statements \(A\), \(B\), and \(C\) was given in lectures by proving \(A \Rightarrow B\), \(B \Rightarrow C\), and \(C \Rightarrow A\), you may be required to prove in Part B of the exam that \(A\) and \(C\) are equivalent, i.e. that \(A \Rightarrow C\) and \(C \Rightarrow A\), noting that \(A \Rightarrow C\) is probably easier to prove than proving both\(A \Rightarrow B\) and \(B \Rightarrow C\).

Some of the question parts in Part B will require original arguments that you may not have encountered before. This is hit-and-miss from student to student, so do not fret about these parts. I found that the hardest question in Part B was usually a question regarding group actions or the Sylow theorems. In particular, classifying group structure with the Sylow theorems was not always very straightforward; Alex does some examples of these in lectures, but it is clear that there is no methodical approach that applies to all groups. (There is also the 50-year classification of finite simple groups in case you are not convinced.)

Occasionally you will be asked in Part B to write down a theorem statement. This is something you should do verbatim, as the wording of mathematical theorems is always very precise, so I recommend memorising all the statements of the major result from each of the topics mentioned earlier. In particular, do not forget smaller details like the requirement for a vector space to be finite-dimensional, a field to be algebraically closed, or whether the existence of something is unique. These are all vital details which taint the accuracy of your statement. Technically, of course, you are simply wrong if you omit anything, because this is maths. On the other hand, do not accidentally add more conditions to restrict the result, because what you state will then not be the required theorem, even though it may still be a true statement.

It helps if you are somewhat familiar with the proofs of these major theorems, because then you may be able to justify the conditions stated in the theorem even if you have not memorised the theorem statement verbatim. For example, the requirement for vector spaces to have finite dimension is because some of the theorems deal with matrices, which are by nature of finite dimension. The requirement for the field to be algebraically closed in the theorem about the Jordan normal form is because we require the minimal polynomial to be factored completely into linear factors, which is not always possible if the field is not algebraically closed.

You should expect to use the major theorem for each topic in Part B for the topics which are assessed, so try and apply the major theorem if you are ever stumped.

GTLA is a long stride away from most other undergraduate maths subjects, but if you are comfortable with abstract theory, then it gives you an insight into a very beautiful area of mathematics. The hard work is there, but so is the satisfaction.
Thoughts on my journey through university
2014–2016 BCom (Actl), DipMathSc @ UoM
2017–2018 Master of Science (Mathematics and Statistics) @ UoM

Maths Forever

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Re: University of Melbourne - Subject Reviews & Ratings
« Reply #632 on: February 15, 2017, 05:21:54 pm »
+2
Subject Code/Name: MAST20030: Differential Equations

Workload: 3 x One Hour Lectures and 1 Problem Based Class per Week.

Assessment: Three Assignments (10% each, totalling 30%) and 3 Hour Written Examination (70%).

Lectopia Enabled: Yes, with screen capture.

Past exams available: In 2016, the course had a new lecturer. The content and lecturing style was VERY different to how it ran in previous years (i.e. 2013 to 2015). As a result, the past exams were available (no answers), but were not so useful. The 620-232: Mathematical Methods exams (still no answers) from 1998 to 2007 were more useful. The lecturer made it clear which questions from all past exams were relevant and not so relevant. The lecturer also provided one practice exam for the current course (with no solutions). This was by far the best guide to what was expected. It was proposed in the SES feedback that in 2017, solutions to the practice exam will be made available.

Textbook Recommendation: There are no prescribed textbooks. The lecturer recommended the textbook ‘Elementary Differential Equations and Boundary Value Problems’ by Boyce and DiPrima if you are looking for a source of questions (since there is no homework problem book prepared like in first year mathematics and Vector Calculus).

Lecturer(s): Dr David Ridout.

Year & Semester of completion: 2016, Semester 2

Your Mark/Grade: H1

Rating: 5/5

Comments: Given that this was David’s first time lecturing the subject, I think he did an amazing job of delivering the course. David wrote the lecture material from scratch for the entire semester. As a result, the lecture slides were continually updated every few days or so. In my opinion, the amount of work that David put into preparing this course was very impressive.

I found that this course had a very good balance. The lectures contained plenty of examples on the theory being covered as well as detailed explanations on the theory behind the main ideas. If you took the effort to understand this theory, you appreciated what you were doing and did not feel like you were ‘blindly’ applying the techniques to solving differential equations. The course was also appropriate to second year level. David’s remodel of the course made it more enjoyable in my opinion. I felt that the content was suitably challenging and motivating throughout the entire semester. It was useful for students in all fields of science whether that be mathematics, chemistry, physics or engineering.

However, you needed to be prepared for the PACE of the subject. We covered a LOT of material in twelve weeks of lectures. David started off the course by reviewing the Calculus 2 content VERY quickly. You also needed to be competent with Linear Algebra concepts, since these ideas were used to motivate the ideas of differential equations.


The course covered five main topics across the twelve weeks of semester:

Linear Ordinary Differential Equations (Week 1 to 3): The first new subject of study was Reduction of Order (in which you learnt how to find a second linearly independent solution to a second order ODE if you already knew the first solution). Other sub-topics included the Wronskian, Higher Order Differential Equations, Systems of First Order Linear ODEs and Series Solutions for Linear ODEs.

Laplace Transforms (Week 3 to 6): This transform was a very useful technique to solve ODEs with constant coefficients, ODEs in which the inhomogeneous term was arbitrary (which introduced the concept of convolution), and solving ODEs in which the inhomogeneous term was piecewise continuous (i.e. had a finite number of discontinuities).

Boundary Value Problems and Fourier Series (Week 6 and 7): This topic covered the basis required for solving partial differential equations (PDEs). You learnt how to solve ODEs in which conditions were specified at the two endpoints of a domain for which the solution was valid (rather than at a single ‘initial’ point as is the case with initial conditions). Fourier series helped to express functions (e.g. x and x^2) in the form of a series solution which involved constant terms, sine terms and cosine terms.

Partial Differential Equations (Week 8 to 10): PDEs are applicable to all sorts of physical situations and, in this course, involve two variables. We studies three types of PDEs in this course; the heat equation, the wave equation and the Laplace equation, subject to suitable boundary and initial conditions. These equations involved differential equations which had partial derivatives (i.e. derivatives concerning only one variable, with the other variable held fixed).

Fourier Transforms (Week 11 to 12): This was the final topic, and probably the most difficult part of the course. You learn how to solve ODEs and PDEs in which there is no boundary on the domain (i.e. the ODE/PDE is unbounded). You explore all the various properties of the transform to help solve such types of differential equations.

PROBLEM BASED CLASSES: These were of the same format as first year Mathematics and Statistics subjects and Vector Calculus. At the start of the tutorial, you receive a series of questions and work on whiteboards in small groups to solve them. These problems are sometimes harder than what you would expect in an exam situation. The tutors are very knowledgeable and the solutions received after the class are detailed.

ASSIGNMENTS: Do not underestimate the amount of time required for each assignment. You certainly have to work hard to get the 10% credit in each of the assignments. They are very long and you are given about three weeks to complete each assignment. You should try to work on the assignment as the material is covered in each lecture. Do not wait until all of the content is covered, since this is typically not until about a week before the due date (and you need more time than that if you want to do well).

EXAM: The exam is pretty fair, and is consistent with the level of difficulty shown in the practice exam. If you have done plenty of practice during the semester and have worked consistently, you should be able to achieve a good final grade.

Even though I am not specialising in applied mathematics, I found this course very enjoyable and engaging. I give the lecturer a huge amount of credit for this. I would highly recommend this subject if you are planning to major in Mathematics and Statistics or are undertaking a major in applied science.

« Last Edit: February 15, 2017, 05:40:47 pm by Maths Forever »
Currently studying at the University of Melbourne.

dankfrank420

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Re: University of Melbourne - Subject Reviews & Ratings
« Reply #633 on: June 21, 2017, 03:34:39 pm »
+4
Subject Code/Name: Introductory Econometrics (ECOM20001)  

Workload: 2 x 1hr lectures per week, 1 x 1hr tute per week

Assessment: 
Optional MST (10%)
2 Assignments worth (10% ea.)
Tutorial attendance and participation (5%)
End of semester exam (65%)

Lectopia Enabled:  Yes, with screen capture

Past exams available:  Yes, 3 were available over the course of the semester. Plenty of review material was also supplied.

Textbook Recommendation:  Don’t know, but you really don’t need it. Lecture slides and tutorial work is sufficient.

Lecturer(s): Joe Hirschberg

Year & Semester of completion: 2017 Sem 1

Rating:  3.5 Out of 5

Your Mark/Grade: H2A [79]  :'(
Comments:

This subject is an introduction into the world of econometric modelling – meaning that the subject is entirely regression based. Don’t let the narrow scope fool you however, as this subject goes far deeper than the brief overview of regression modelling that was taught in QM1.

The first month of the course is easy enough, as it’s mainly an overview of what was taught at the end of QM1. The assumptions underpinning the OLS model, using t-tests, hypothesis testing, constructing confidence intervals etc. After that, it sort of ramps up a bit. You learn all these different types of tests on data, how to model binary independent and dependant variables, the effects of heteroskedasticity and collinearity, and finally you do a little bit of analysis and breaking down of time series data.

Throughout the semester, you’ll be using a program called E-Views which basically runs your regression for you and gives you data on its strength, errors etc. It’s not too hard to get your head around, which is good because it features heavily in assignments and some E-Views output is put on the exam for you to analyse.

Lectures

Lectures are actually alright in some areas. Joe usually introduces the concept, derives the formula/test/distribution, then provides some real world example and intuition using the aforementioned E-views output. Like QM1, they can get a big jargon-y at times, so you have to really pay attention to know what’s happening in each step. Given the nature of the subject, it can get a bit dry at times but it is satisfying to see why stuff works the way it does and how it all clicks together. Joe also does get through some practise questions using the topics you’ve just learnt too, so that was helpful as well.

Tutorials

Tutorials consisted of going through a few questions each week using E-Views. The questions were basically “here’s a regression for this model, analyse it using this technique/test”. As such, questions get repetitive over the course of the semester. I found that the tutor always rushed through the answers so I never really got it while I was in the class itself, but once I went home and reviewed everything it started to make a lot more sense. There’s also 5% in tutorial marks for attendance, so if nothing else go for that extra boost to your score.

Mid-sem test

About three weeks into the semester you do an optional mid-semester test with counts for 10% if your mid-semester test score is greater than your exam score, so you might as well do it. The test itself isn’t too bad, just 12 MC questions on the basic regression models and the assumptions underpinning it. Most people I know got 9+, it wasn’t too challenging at all.

Assignments

The assignments aren’t too bad. They include a question from a past exam that tests your understanding of certain formulas, while the rest of the assignments are running E-views regressions and analyzing the output using different tests. They do take alot of time, as there is alot of graphing and constructing regression equations involved. While the questions aren't too difficult,they are pretty lengthy and time-consuming so don't leave it till the last minute.

Also, there's a section on programming in E-Views, where you've got to write E-Views code for things you already know how to do using the buttons on E-Views itself. The problem here is that they don't actually teach you how to write code in tutorials or lectures, so it's pretty much entirely up to you to learn it. They don't assess it in the exam either, so I found this part pretty frustrating and unnecessary - difficult for the sake of being difficult.

Exam

The exam itself was pretty good I found. 2017 semester 1 was the first semester that all FBE subjects are a hurdle (new policy), so I think the lecturer acknowledged this and made the exam not too difficult. There were a few multi-choice and true/false questions, then some short answer questions where you’ve either got to manually run a regression or analyse some E-Views output and run tests/comment on it.

There were enough easy questions in there to pass quite comfortably, but some questions were pretty tough so getting a high score is quite difficult.
That being said, the short answer questions format is extremely similar to the past exams/review sheets that Joe hands out, so if you can get through those and understand the content you’ll be set for high marks.

Overall

This subject serves as an introduction to econometric modelling and one of the pathways you can take if you want to major in economics. It can get a bit overwhelming at times (sometimes Joe will rush through slides and you’ll have no idea what’s going on), but on reflection the subject was pretty repetitive. If you can nail down the core principles (understanding the basis for a regression model and the tests we use on them) then you’ll be in a good place come exam time. All the tricky stuff at the end of the semester is really just an extension of the basic stuff you learn at the start of the semester, which isn’t too hard to grasp if you managed to get through QM1.

Good luck!
« Last Edit: July 09, 2017, 03:27:14 pm by dankfrank420 »

wobblywobbly

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Re: University of Melbourne - Subject Reviews & Ratings
« Reply #634 on: June 23, 2017, 12:06:15 am »
+5
Subject Code/Name: ECON10002: Seminar in Economics and Commerce A 

Workload:  2 x 1.5 hour seminars weekly

Assessment:
2 assignments, marked out of 25, weighted 25% each (total of 50%)
1 examination (50%)

Lectopia Enabled:  No, due to the nature of the subject.

Past exams available: Sample exams were not given, however they are available in the Bailleu Library.

Textbook Recommendation:  "The Worldly Philosophers" by Heilbroner, available at the Co-op. Recommended as readings are required for a full understanding of the subject. More readings will be given to you by Robert, as in he will print them for you.

Lecturer(s): Professor Robert Dixon

Year & Semester of completion: Sem 2, 2016

Rating: 4 out of 5

Your Mark/Grade: H1

Comments:

Note: This is a quota subject that accepts approximately ~25 students. You must have completed a maximum of 50 points and one semester when signing up for this subject. For more information on how to apply, see here on how to sign-up.

Summary
The subject is completely different to what you have done so far in university. It is a subject that focuses on the history of economic thought and political economy from Adam Smith to Keynes, Friedman to Marx. There is also a bit of crossover with Introductory Macroeconomics throughout the semester, which you may or may not find useful when you're doing it simultaneously.

You will get a list of things you will study in the first seminar (note this changes throughout the years, so you might not learn exactly the same things we did), but the this list will get reordered around depending on how the class goes with the topics -- there is a large variety of them. We learnt about Adam Smith's Wealth of Nations, Malthus, Say's Law, the Cobb-Douglas production function, the model of the real wage/wage share, Keynesian theories on demand, implications of monopoly power, Walras' Law, Domar's and the Solow-Swan model of growth, and Milton Friedman's explanations on unemployment and inflation.

Seminars
The first thing that's different about this subject is the seminars. Instead of the typical FBE subject structure of 2 x 1 hour lectures and an hour of tutorial, it is 2 x 1.5 hour seminars. At the start of each lesson you'll get a hand-out of what will be covered (which is also posted on LMS), but in a typical seminar what it generally asks with questions about the previous seminar, answering the set questions in the previous seminar, then reading and discussing the reading for that seminar. Sometimes there is additional reading to be done outside of class, either in Heilbroner or again, in the hand-outs. It's best to prepare for the questions because he will go around the class and ask each person to answer a question (although you can refuse to answer if you don't want to, but it's not a good look). Sometimes you'll watch a movie (e.g. about Keynes) instead of the discussions. Robert clearly knows his stuff, is sometimes hilarious, and has been at the university for ages. Of course, because of all of these discussions, it's quite difficult to record, so there is no lecture capture. If you can't go to a seminar, just ask a friend to borrow their notes for the lesson. All of the hand outs are on the LMS anyways, so you're missing out on the answers and the discussion.

Assignments
There are two assignments which can be done in groups of up to four, and both are worth 25%, giving them a 50% weighting. You'll typically receive them a few weeks in advance. You're encouraged to work in groups because these questions require a lot of thinking and discussion to get through. It is compulsory to meet with Robert beforehand in a consulation to discuss the assignment in-person before submission (maybe a week in advance). This means you should complete your assignment ASAP so that you can fine tune it before you bring it in to Robert where he discusses where you may have gone wrong in your reasoning. Just don't write things carelessly because there's been stories of him roasting people :P These discussions are absolutely helpful because he gives hints and tips on how to do well on the assignment, but he won't help you if you haven't written anything down, so do so. Because of this, it shouldn't be too hard to do well: most, if not all of the class got above 90% combined. In the second 'consultation,' he'll also sit with you and talk about what you want to do in UniMelb and give you subject recommendations based on what you tell him.

Exam
The exam is weighted 50%. Robert will tell you which seminars to focus on for the exam, including their associated hand-outs/readings and related assignment questions. One of the questions on the exam which will be worth about a third, will be based on a reading that is given in the very last seminar, and you will also know that exact question in advance as well (i.e. exactly what will be asked). Prepare for this question, but obviously you can't ask Robert to check it for you because that would be unfair. The exam was very fair and there weren't any nasty tricks or anything like that.

To sum up
Definitely give this subject a go if you're given a chance. This is a subject that really pushes your understanding of economics, and helps keep you informed about the different schools of economic thought, (e.g. the Chicago school of economics) something which isn't covered by the normal economics subjects. The content crossover into Introductory Macroeconomics was definitely useful to understanding how those models were arrived and reached at, as well as their criticisms and critiques instead of just learning what they are and how to use them. When I took this subject, Robert was also teaching Macro as well, and I do recall that Seminar helped us with some of the assignment questions in Macro. Robert is an outstanding lecturer too. We liked Robert so much we bought him a few presents in the final seminar.
« Last Edit: June 23, 2017, 12:08:54 am by wobblywobbly »
:)

M909

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Re: University of Melbourne - Subject Reviews & Ratings
« Reply #635 on: July 01, 2017, 05:45:25 am »
+3
Subject Code/Name: MAST10008 Accelerated Mathematics 1
Workload:  4×1 hour lecturers per week, 1×2 hour 'tutorial' per week (A prac, followed by a computer lab session - must be in this order, together in a 2 hr block)
Assessment:  3 written assignments (9%), 3 online assignments (6%), 45 minute MATLAB test (5%), 3 hour end of semester exam (80%)
Lectopia Enabled:  Yes, with screen capture
Past exams available:  Pretty much all the past papers for this subject can be found on the library website. The solutions for the past 4 papers were placed on the LMS near exam time. Also, a sample MATLAB test without answers was provided
Textbook Recommendation:  Elementary Linear Algebra, Applications Version (H. Anton and C. Rorres), 11th edn, Wiley, 2013, is recommended. IMO it doesn't need to be purchased, the lecture slides and work book that is provided is enough.
Lecturer(s): Craig Hodgson
Year & Semester of completion: 2017, Semester 1
Rating: 4 Out of 5
Your Mark/Grade: H2B (74)
Comments: Overall: As the subject name suggests, this is a fast paced and difficult subject, however if you like maths and you're willing to put in the effort, it's an interesting subject that will teach you many new concepts. Also, a book of practice questions is on LMS at start of year which is an awesome resource.

Lectures: Personally, I found the 4 hour/week load a lot to take on as a new Uni student. In hindsight, if I knew how the AM1 lectures operated, I would have only attended Uni 2 or 3 times/week, and watched the rest at home (Craig records everything, so unless the capture wasn’t working – happened once – you can pretty much get everything at home. However, I’d heard this is not the case for AM2, and you must attend these unless you can self-teach yourself). In terms of the content, be prepared to not understand a t lot that goes on when it’s first presented to you – understanding will usually take you to really look over notes, do practice questions, rewatch lectures ect. I know a lot of people said they had no idea what was going on in lectures. However, if you put in this effort, thinks eventually come together, although you must keep on top of it due to the fast pace.

Tutorials: I would highly recommend going to all tutes, even if you’re not understanding the content yet. You received a sheet (and full worked solutions), and work through it on the board in groups. Obviously it’s not the end of the world if you miss a session as you can get copies of these from a friend, but IMO the tutors input really helps, especially with regards on notation/setting out, which they’re really picky about in assignments and the exam.

MATLAB: I’m not really qualified to say much here as I failed the test, but you have a lab after your tute once a week. MATLAB is basically a big calculator, and the lab teach you the basics, then go into different concepts, some related to lectures and some not. The test will be on concepts learnt in lectures with usually one programming/’create m-file’ question; make sure you’re on top of these for the test - you may have to do extra research. 

Assignments: There are two types of assignments – online and written. IMO, online assignments are the closest thing you get to a participation mark. If you’ve kept up to date and can do the basics, full making them is very possible, as you get unlimited time (up to due date) and three attempts. Written assignments are a lot tricker, and you should be pedantic about notation, and there’s usually at least one very difficult question.  But again, good scores are possible if you’re on top of it.

Exam: Most likely due to the difficulty of the subject, most the questions are just straight up theory based. It is non-calculator, so make sure you can do everything by hand. It’s a big chunk of the subject, but usually they are enough ‘basic’ questions so that if you’ve kept on top of everything, you can put at least a 70, with some very difficult questions to separate the cohort. Personally, I had a bit of time, but made some very silly mistakes, so be careful with your answers!   

M909

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Re: University of Melbourne - Subject Reviews & Ratings
« Reply #636 on: July 01, 2017, 06:31:04 am »
+3
Subject Code/Name: FNCE10002 Principles of Finance
Workload:  1×2 hour lecturer per week, 1×1 hour tutorial per week
Assessment:  Tutorial participation (10%), Assignment (10%), 1 hour Mid-semester exam (20%), 2 hour end of semester hurdle exam (60%)
Lectopia Enabled:  Yes, with screen capture
Past exams available:  No, as it is a new subject. However, two sample exams with solutions were provided for both exams, and exam questions from similar subjects are put in tutorial work.
Textbook Recommendation:  Berk, J. and DeMarzo, P., Corporate Finance: The Core, 4th ed is the main one you need. Principles of Corporate Finance, 12 th ed is optional, but not needed.
Lecturer: Asjeet Lamba (Lecture apparently changes for semester 2 though)
Year & Semester of completion: 2017, Semester 1
Rating: 4.5 Out of 5
Your Mark/Grade: H1 (87)
Comments: Overall: This subject, along with ARA and micro, was a great introduction to commerce for your typical maths/science high school student. I really enjoyed the maths in this subject, as well as the introduction to the stock market. It can get tricky at times, but it’s not an overly hard subject and if you put the effort in good grades are very achievable. The only reason I gave it 4.5 instead of 5 was because sometimes there were exam questions requiring you to remember diagrams/graphs in lectures, however you could usually alternatively figure it out with some understanding. 

Textbook: I would only recommend Corporate Finance: The Core, although you can honestly probably get by without it. The reading gets a bit much every week, and I personally didn’t understand a lot straight away. However, doing the pre-reading can help you get a preview before lectures, and can complement your understanding.

Lectures: Not everything will make sense straight away, but lectures definitely aid your understanding. Asjeet goes through the theory with exams, as well as case studies, showing you how it’s applicable to real life. I’d recommend attending, or watching at home, whichever works best for you.

Tutorials/Tutorial participation: The participation mark for this subject is IMO a lot more objective than others. You need to attempt some questions, and hand it in to your tutor, and you need to hand in 8/10 for full marks – should pretty much be a guaranteed 10% if you’re trying. It doesn’t matter if you make mistakes, as long as your tutor thinks it’s an attempt – even if you’re not understanding yet you can just sub some values into a formula and still get full participation marks :) Tutorials involve you discussing questions you’ve been given the week before to work on, and your tutor then taking everyone through the answers. Answers uploaded to the LMS are minimal, so I’d recommend attending, and definitely stay on top of pre-tute work.

Assignment: Pretty much a take home multiple choice exam, but with easier questions. If you’ve got the basics, can easily be full marked (at least the semester I did this subject).

Exams: A formula sheet without descriptions is provided, however it is not just about plugging in numbers – you need to understand what the formula is doing, and well as theory behind the stock market, companies ect. The exams are quite a bit more difficult than the assignment, but once you put everything together it’s not too hard. Ultimately, this subject just requires consistent effort.

Alter

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Re: University of Melbourne - Subject Reviews & Ratings
« Reply #637 on: July 01, 2017, 10:57:43 pm »
+3
Subject Code/Name: PSYC20006 - Biological Psychology

Workload:  2 x 1 hour lectures per week, and 1 x 2 hour tutorial every second week

Assessment: 2000 word lab report split into two evenly weighted sections (each 1000 words and each worth 20%), due in weeks 5 and 9 (40%), 2 hour exam consisting of 120 MCQ (60%)

Lectopia Enabled:  Yep

Past exams available: No past exams, but the quizzes on the LMS are very similar to the exam and should be used like past exams

Textbook Recommendation: Physiology of Behaviour is prescribed, but never really mentioned or used. All of the information that you need is in the lecture slides.

Lecturer(s):
Stefan Bode - Brain Imaging Techniques (2 weeks)
Piers Howe - Brain Imaging Techniques (1 week) and Statistics (1 week)
Jacqueline Anderson - Neurobiology of Memory (2 weeks)
Patrick Goodbourn - Neurogenetics (2 weeks)
Olivia Carter - Psychopharmacology (4 weeks)

Year & Semester of completion: Semester 1, 2016

Rating: 4.5 out of 5

Your Mark/Grade: H1

Comments:
I thought it'd be a good idea to revamp the subject review for this, because a couple of the lecturers have changed with a new topic being introduced since Paulrus did his review, but I'll leave it in the same format. My sentiments mostly echo previous reviews in the sense that this is a really great subject with a manageable workload that I'd recommend to anyone that's capable of fitting it in their study plan. For context, I did this subject as a Biomedicine selective without having done MBB1/2.

Lectures:
Stefan is the new subject coordinator for Biological Psychology and he is a widely-loved and entertaining lecturer. He has a funny and extraordinarily engaging lecture style and really delivers the content in an enthusiastic way. Stefan covers the use of transcranial magnetic stimulation and the EEG with four lectures overall. There's not too much to say here outside of the fact that Stefan is one of the reasons why this subject is so great. He also has a beautiful German accent.

Formerly, Piers was subject coordinator and did Stefan's part of the course as well. It seems like he got the short end of the stick teaching the two areas of the subject that people find particularly dreadful: physics (of the fMRI) and statistics. In all honesty, Piers is a pretty solid lecturer and he does a great job with the content he teaches. It's obvious he knows what he is talking about. I think that it's fair to say that you might need to do an extra bit of work for this part of the course depending on your background. Having done Physics for Biomedicine and EDDA (level 1 stats subject), I was pretty comfortable dealing with the little bit of physics and statistics that is covered; however, I think these areas are totally manageable even without that background. The statistics part of the course is basically just preparing you for the assignment and you need to be able to do t tests and understand the different ones, really not much to worry about.

I think Jacqueline's section is fairly straightforward. It's probably fair to say that as a lecturer, she isn't quite as engaging as the others, but there's nothing particularly bad about her as a lecturer. The content itself is quite simple, and if you've done VCE psychology you'll find that you've already done half of the stuff before, which is a nice bonus. Make sure you understand all the different types of memory and memory systems, because you need a solid foundation of understanding for this part of the course.

Patrick Goodbourn, another new lecturer, is very witty and clearly a huge expert in his field. It's also probably fair to say that his section of Biological Psychology is the hardest one. I was extraordinarily grateful to have come from a Biomed background with genetics subjects, because he really expects you to understand what's going on when he's talking about genetics, and his questions will be impossible if you only have superficial knowledge. Overall, I'd be willing to say that neurogenetics was probably the most interesting topic I've covered at uni, but learning it will not come easily. Be warned that you will need to write down A LOT of information that he doesn't say, because his slides are simply barren. This isn't necessarily a bad thing, but it can make it quite tricky if you're unsure what you actually need to know. If you have no biology background, this will be tricky.

Olivia is another great lecturer and she covers psychopharmacology. You will see based on the number of lectures this topic has that this area will be hugely important for the exam (it's basically 1/3 of the course... so learn it well). Olivia is super engaging and will basically start off with an overview of how psychopharmacology works, and then delve into a bunch of different neurotransmitters that you're expected to know and understand. 

Tutorials:
The tutorials are pretty cool, but are mostly just there to help you with the assignments. One of the tutorials will involve you changing room to go to a computer room where you use SPSS to do data analysis for your lab report, and it's extremely important you pay attention to what's happening here or you'll have issues down the track. My tutor was a really awesome dude who was actually doing work in Stefan's lab, and basically gave us tons of tips on doing psychology because he was in our position doing Biopsych a few years back. If anything, I'd advise you to use your tutor as a resource if you (a) want to do well in the assignments, because they mark it; or (b) want to know more about psychology at Melb uni.

Assessment:
The previous review mentioned the lab report changing, which I believe will be applicable for those doing this subject in 2018, so I'll save the time by not going into the details and instead give some tips. My general advice for the assignments is to make sure you don't neglect the value of strong scientific writing (it's not just about regurgitating sentences) as well as the importance of doing all your referencing properly. Everybody thinks they'll be fine for referencing, but virtually nobody gets full marks for it. Staff have really put a ton of effort into making sure there are resources for the assignments, and the head tutor Annie even took "classes" for questions about each of the assignments. At the end of the day, you are thrown into the deep end a bit if it's your first APA lab report, so take your time and start the assignments ASAP or you'll get destroyed.

Fortunately, the exam is all MCQ, which is one of the greatest parts of this subject. In terms of difficulty, I think the exam was overall pretty fair, but did have a few questions that ended up getting removed, so my advice is not to stress too much if you think there's no correct option and move on to the next. Also: spam the online quizzes over and over, and really make sure you are capable of questions like them, because the exam is almost identical in question style. I think Patrick's section had some really tough questions; if it wasn't obvious already, just because he only takes 3 lectures does not mean his section is a walk in the park.

Great subject. Do it if you're in Arts, Science, Biomed, or whatever. Good luck!
2016–2018: Bachelor of Biomedicine (Neuroscience), The University of Melbourne
2019–2022: Doctor of Medicine, The University of Melbourne

Elizawei

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Re: University of Melbourne - Subject Reviews & Ratings
« Reply #638 on: July 14, 2017, 11:03:51 am »
+8
Subject Code/Name: FNCE 10002-Principles of Finance

Workload:  One weekly 2hr lecture, one weekly 1hr tutorial

Assessment:  One take home assignment (10%), tutorial participation- weeks 2 - 12, (10%), 1 hour closed book mid-semester examination (20%), 2 hour end-of-semester examination (hurdle) (60%)

Lectopia Enabled:  Yes, with screen capture etc.

Past exams available:  Nope, new subject as of 2017. However Lecturer provides 2 sample exams both before the mid sem and before the final exam.

Textbook Recommendation:  Berk, J. and DeMarzo, P., Corporate Finance: The Core, 4th ed (Extra readings is provided by lecturer)

Lecturer(s): Asjeet S. Lamba for semester 1, Howard Chan in semester 2

Year & Semester of completion: 2017, Semester 1

Rating: 4.5 Out of 5

Your Mark/Grade: H1 (83)

Comments:
I am actually a Biomed student taking this as my first breadth subject. Definitely will recommend to other students as breadth if you're interested in a beginner's subject for finance! Due to Finance 1 only being available in Summer term, this subject is pretty much the equivalent of Finance 1 (FNCE10001). I think with enough work it should be an moderately "easy" breadth (no subject is inherently easy!). Workload during semester was minimal (compared to my other subjects) and it's overall not an intense subject.

Lectures: Excellent lecturer (Asjeet), however lectures can be fast paced and difficult to follow (especially after midsem) I did not attend much lectures after midsem and resorted to LecCapture and going slowly with the lecture notes. Asjeet does like to put in lots of case studies relating to current affairs which makes it engaging and interesting.

Tutorials: For me SO IMPORTANT without them I would not have understood. The tutor goes through all the pre-tute questions except for the part you have to hand in. The hand-in component is very small, would only take about 10 minutes (provided you know what to do! :P) Also the marks are for participation, there were so many tutes where I knew it was totally wrong but bsed my way through, they reward you full marks as long as you give it a good shot. You'll have to hand in 8/10 tutorial questions with decent attempts to achieve the full 10%, which is guaranteed imo provided you don't forget. Attendance is taken, however I found them to be extremely useful and recommend you to go to all of them.

Exams: Exams are more or less the same standard as the sample exams prvoided on the LMS. Mid sem exam can be difficult if you were purely preparing for application and not theory, however with adequate preparation you will do well. :) Formula sheets are provided for both exams but without descriptions. The final exam covered content from mid sem onwards, but of course many basics are incorporated in the more complicated calculations. 

TLDR: awesome subject (especially as a lvl 1 breadth for those who like easy maths and finance), 10/10 would recommend.  ;D

ATAR: 99.70
2017-2019: Bachelor of Biomedicine [University of Melbourne]
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Re: University of Melbourne - Subject Reviews & Ratings
« Reply #639 on: July 24, 2017, 07:59:50 pm »
+3
Subject Code/Name: ITAL10004 Italian Mid-Year Winter Intensive 

Workload:  4 days (Mon-Thurs) x 3 weeks - 2x 2 hour tutes per day, two different tutors assigned to each class

Assessment:  8x2.5% daily quizzes, 10% listening, x2 assignments (x10% each), Exam (40%) , Participation (10%)

Lectopia Enabled:  No, only in class tutorials

Past exams available:  No - this doesn't matter because you'll have enough in class practice.

Textbook Recommendation: 

Textbook - Salve 2nd

Some people didn't purchase the book but wrote down notes from class - which I think is suffice because the power points are informative  but this depends if you take good notes. I found the textbook good to note down practice examples and convenient to have instead of sharing in class. The activity book is great - with languages practice really does make perfect!!! So I highly recommend getting photocopies (it's in the library) of the exercises or getting the book/s (they'll put answers up on the LMS! Make sure to make note of your mistakes!)

Lecturer(s): Matteo - coordinator; Tutors: Beatrice, Danielle, Brent, Nick, Riccardo, Antonella

Year & Semester of completion: Winter 2017

Rating:  4.9 Out of 5 (0.1 off bcs well at times I was adfjalsd because of not being able to pick things up quickly but it is an intensive after all, and that's why you have downtime to self study and revise! That's just me.)

Your Mark/Grade: High H1

Comments:

Honestly the best subject I've completed during my undergraduate degree! Whether you love languages or not, I think anyone can pick it up given a reasonable amount of study and of course staying on top of your work because it is an intensive. Don't let the idea of an 'intensive' deter you from choosing this subject!

In class you do learn about grammar and vocab. You get to practise talking in Italian in partners and answer textbook questions. We also had the opportunity to visit an Italian Museum and watch an Italian Movie which was great - kept the intensive exciting!

"Intensive"

I'm not going to lie ...during the first week I was at times disconcerted because of the pace. Well the issue I had was answering questions when being picked on and I was lost or had to look at my notes to answer. Because of this I was seriously going to change breadths - but thankfully I did not! Yes you will be confused at times but once you get the day off you can revise and review everything. Or even better you ask the teacher right then and there 'I don't understand, please explain.'  I'm not a fast learner so to have Friday and the weekend off is great - I connected the dots together and self studied (which works best for me vs understanding things on the spot). So if you're like me bear through the day and revise at night to consolidate everything (learning a language does require patience, this is normal)! Futhermore because this is Level 1, despite it being an intensive there isn't much to cram because you learn things > practise them in class> get tested on content from the day before> so you really will be on top of it - ALSO big bonus everything is fresh for the exam, it was just some light revision and practice for the exam.

Teachers/Tutors
All the teachers are lovely and seem like they love teaching! No kidding! Matteo the coordinator is chill and happy to answer questions or deal with any concerns! He says that last year the cohort was ~40 and this year ~90 and he really wants to promote this subject for future years...probably why a lot of people did well too haha The tutors are really approachable and I think definitely ask for help in class then and there if they're going too quick! Just say 'Una domanda!' :D

Assessment:
8 daily vocab tests
They are easy to do well in. They test what you've learnt from the prior day. Most are one paged, all quizzes are short. There was one with comprehension qs too - it has basic sentences you already know. Advice: Revise all vocab, grammar from the day before

x2 Assignments:
Straightforward. They have two components: Part A is grammar e.g fill in the blank, Part B: Write a short passage (approx 60 words)
By the way they take Academic Integrity seriously (ofc) -make sure you don't google translate stuff.
Hot tip: Use simple, basic sentences you have learned in class. Even if it's "Venice e una citta molto bella" = Venice is a very beautiful city. Simple but enough to get you marks. Believe me!

Listening test

The teacher reads the passages (they are short!) out - clearly and with a decent pace too. The questions are MC true/false. Once again it's pretty easy as long as you got the vocab down. 

Participation:
They mark this fairly IMO but it's not just for attending class. They give you a rubric. Tutors go around the class to ask for answers (don't fret, everyone has to respond and don't worry if you don't know -- because it's an opportunity to learn) - but I think you have to actually give your opinion (e.g about the movie/videos you watch during class) to get H2A or H1. It's seriously ok if you can't form complete Italian sentences ( e.g What was this ad about? How does this ad portray Italians?) - just try in English if you can't!!! They'll help you out and everyone's a beginner.

Exam:
They prep you well for the exam - no kidding! They'll go through writing exercises that will aid you in the actual exam - you get an opportunity to test out your writing, the teacher will come around and correct your mistakes. I think the best advice I can give is: Practice makes perfect or Do the exercises in the Activity Book! The exam questions are really similar to the ones you get in your daily quizzes. From memory it was divided into Comprehension (True/False),  Grammar and Writing.

I could write moreee...but if you have specifics please feel free to inbox me with questions etc :) And please give this breadth a try - you might love it enough to continue on to Italian 2!  ;D




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Re: University of Melbourne - Subject Reviews & Ratings
« Reply #640 on: July 25, 2017, 07:59:46 am »
+5
Subject Code/Name: PHYC10001 Physics 1: Advanced
Workload: 
3x 1 hour lectures
1x 3 hour practical
1x 1 hour tutorial

Assessment:
15% - 10 weekly homework assignments (1.5% each)
25% - 8 weekly practicals (5% was prelabs, 20% was the prac and writeup) Hurdle, need to attend 80% of labs and get 50% average.
60% - 3 hour end of semester exam

Lectopia Enabled:  Yes, with screen capture

Past exams available:  Yes. Exams from 2011-2016 with numerical answers (not detailed answers or working)

Textbook Recommendation:  Halliday & Resnick, Fundamentals of Physics, 10th ed., Wiley 2014. Not required but the lectures were difficult to follow, so I'd recommend getting a version of this book (9th edition and earlier are much cheaper).

Lecturer(s): David Jamieson for the first half (kinematics, motion) - enthusiastic but goes too fast for the class
Robert Scholton - second half (special relativity, gravitation, waves etc) - similar problems but tends to go a bit slower

Year & Semester of completion: 2017 Semester 1

Rating: 2 Out of 5

Your Mark/Grade: High H2A

Comments:
Being brutally honest - this subject was not done well. This subject may change in the future, but when I did it this semester it wasn't taught well, went too fast, and was very disorganised.

Pracs:
These pracs were timetabled in for 3 hours but it was usually 10 minutes or so of explanation, and around 2 hours of doing the prac and writing it up. So, the pracs usually finished around half an hour early (one demonstrator said no writing after 12:30, the other helped us out and let us have extra time).
These pracs were usually where we learned the content. We often learnt the subject material in lectures around 2 weeks after we had a prac on it. There is also pre-lab work, and it can take a while to wrap your head around the pracs and concepts. Usually there were 2-4 sections of the pracs to complete, and you were lucky if you got 2 parts done. Each is like a separate prac and you will be rushing for a lot of it. In my pracs, most of the marks were from the analysis, regardless of how far through you got, so leave plenty of time for this. The amount of content that needed to be completed was ridiculous, the descriptions of the pracs were confusing, and it was often on new content we hadn't been taught. Pracs were a major source of stress for me.
The prelabs, though, are the easiest marks you can get, basically a free 5% for the subject. Takes 5 minutes or longer if you're researching the answer, and it's 3-4 multiple choice questions with some obvious answers.

Tutorials:
Some tutors were better than others. In my class, we did our own work while our tutor walked around, checked up on how people were going and answered questions. When things were explained, they were explained in a very complicated way that was difficult to understand. I found this very unhelpful, but I'm sure other classes were better.

Weekly Assignments:
10-13 online questions. They took 3-10 hours per week but were good marks if you were willing to put in the time relearning content and sticking with it. You were given 3 chances to get the right answer, so that was good. The questions were often confusing and difficult but the assignments did relieve a bit of the pressure off from the exams. The questions are by the textbook manufacturers not the lecturers, so they can end up being difficult.

Lectures:
The lecturers often went through concepts too fast and didn't explain things well. They seemed to like physics, just being a bit lacking in the teaching area. I didn't feel like I learned any more by being in the advanced, if anything I learned less. The lectures were also at inconvenient times - there was only one stream (half full). There was limited time for each topic (think we spent 1.5 lectures on special relativity, around 2-3 lectures for other topics). The demonstrations were enjoyable, the best part of lectures, but again not explained well. The lectures tended to go through things very fast and the lecture notes were difficult to understand, with very few examples. I walked out of many lectures having no idea about what they just taught. They also had a lot of "aside"s, where they talked about things not particularly relevant to the course. While these were interesting, they reduced the time we were taught assessable content.

Exam:
I calculated that I needed 23% in the exam to pass, and I'm not even sure whether I got that. The fact that I received 79% overall shows the massive scaling they had to have done on the exam - I'm doubtful anyone passed. It was difficult even if you studied for hours/days/weeks/months. It covered things we hadn't really been taught and didn't have any standard questions, just lots of hard ones. They had to have a similar / higher mark than the regular physics for this subject though (as there was a higher caliber of students) so they had to scale it, I expect by 50% or more.

Overall
I don't know anyone who's continuing on with advanced this semester - if you're thinking of doing it, wait until they have things organised. I'd recommend doing the regular, it's larger with more support and more understandable classes. Overall, this subject was disorganised, difficult, and not worth it (was my lowest mark by quite a bit). I was expecting this class to give me more insight into physics and how things were derived, but it seemed to be an excuse to not explain things properly.
« Last Edit: July 25, 2017, 08:46:27 am by Shadowxo »
Completed VCE 2016
2015: Biology
2016: Methods | Physics | Chemistry | Specialist Maths | Literature
ATAR : 97.90
2017: BSci (Maths and Engineering) at MelbUni
Feel free to pm me if you have any questions!

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Re: University of Melbourne - Subject Reviews & Ratings
« Reply #641 on: July 25, 2017, 08:44:07 am »
+3
Subject Code/Name: MAST10006 Calculus 2

Workload:
3x 1 hour lectures
1x 1 hour tutorial

Assessment:
20% - 4x 5% assignments due on Mondays at regular intervals
80% - 3 hour end of semester exam
There is no hurdle for this subject

Lectopia Enabled:  Yes, with capture. All streams are recorded.

Past exams available:  Yes, from 2013 onwards, both semester 1 and 2 exams with answers  and short explanations provided.

Textbook Recommendation: Don't worry about a textbook, the lecture slides were well done and I never required a textbook. If you need one though, you could always borrow one from a library.

Lecturer(s):
-Dr Iwan Jensen (subject coordinator) - good pace, completed the lectures on time and covered enough so that we were always where we were supposed to be.
-Dr Daniel Murfet - he went faster than required, and so his stream had a week or two where they learned nothing of relevance later. He was a bit more difficult to understand than the other lecturers.
-Dr Joyce Zhang - I rarely attended her lectures, she was alright, had friends who said she was good though.
-Professor John Sader - enthusiastic, often completes the lectures early but does it in a way that is easy to understand.

Year & Semester of completion: 2017 Semester 1

Rating: 5 Out of 5

Your Mark/Grade: High H1

Comments:
Lecture Notes + Lectures:
These were amazing. You could purchase them for around $10 from the Co-op, and they were pretty much mandatory to have. They were organised, and easy to understand. They had the content first, in easy to understand format, and formulas clearly displayed. If explaining needed to be done, it was explained (usually through solving equations) in the next pages and were also gone through by lecturers. After the content / relevant formulas / explanations was done, there were (many) examples. Lectures often had the first 20min or so of explanations, then the remainder was examples where they worked through questions (exam questions were very similar) at a good speed, explaining each step and giving you enough time to copy down, at a pace where you could follow the examples. This may sound boring but they didn't overload us with information and helped us understand how the formulas etc were to be used, instead of just throwing information at us. In my opinion, the lecturers were quite good

Tutorials:
We were given a tutorial sheet to work through. We worked in groups of 2-3, answering the questions on the whiteboard. Often you would alternate who was writing / completing the question with the other/s looking and picking up mistakes, giving advice, helping when you got stuck. It was difficult to get through all the questions but I'm not sure they were designed to be completed in time, or to make sure we had enough to work on. The tutor walked around, explaining mistakes, what we needed to include, incorrect notation, or a good job. If something was commonly done wrong, he sometimes got everyone to listen while he did a short explanation of what to do and why. The tutorial questions are very similar to exam questions, so make sure you do go to tutorials and try to better your understanding of the content. If you didn't understand the content after the lectures, you should mostly understand it after tutorials. If you got stuck, you could work with your group to solve it, meaning time wasn't often wasted just staring at it. The tutorials were quite enjoyable and helpful.

Assignments:
The assignments were often semi-long but straightforward. Be warned, they are very pedantic, and you will often lose marks for small mistakes such as not putting in a couple arrows. Some questions can be difficult, so make sure you don't leave it until the day before. I've heard some people just plugged the question into Wolfram Alpha, but this won't allow you to do well in the exam, it's much better to solve it yourself and use a program to check your result if needed. Most of the marks are for working, not the answer. Make every step and all justifications very clear. However, if you put in the work you should be able to do well. I recommend writing a rough draft of your answers during the week to make sure you know how to solve each question, and writing out a proper copy on the weekend (earlier if you have time) with the proper notation and justification.

Exam:
The exam was relatively straightforward and similar to past exams. There weren't really any "super tough" or "shock" questions, some were more difficult than others but the exam was there to test your knowledge not to trick you. If you properly prepare beforehand, you should complete the exam in time (I had about half an hour left, but many others didn't). The structure of the exam is often similar to past ones - it's worth it to do a couple past exams before your exam. Usually around 10 questions, pretty much one on each topic with 3-6 parts each, worth around 120-150 marks total. This exam is worth most of your mark, so study hard for it. If you worked hard on the assignments though, you don't have to do as well to pass the subject.

I've heard this subject has a high fail rate (40% or so) but if you put the time in, you should be able to pass without too much trouble. Make sure you don't miss lectures, or if you do then catch up straight away. Never get into a situation where you're skipping classes to catch up on a previous one. The people who are stronger in maths will find this subject relatively straightforward but with enough to keep them interested, and the ones not strong in maths will find it difficult but taught at a pace that they can keep up with. I quite enjoyed this subject, it was taught well, well organised, and interesting without being overly difficult.
« Last Edit: July 25, 2017, 08:48:18 am by Shadowxo »
Completed VCE 2016
2015: Biology
2016: Methods | Physics | Chemistry | Specialist Maths | Literature
ATAR : 97.90
2017: BSci (Maths and Engineering) at MelbUni
Feel free to pm me if you have any questions!

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Re: University of Melbourne - Subject Reviews & Ratings
« Reply #642 on: July 25, 2017, 09:26:54 am »
+4
Subject Code/Name: FNCE10002 Principles Of Finance

Workload: 
1x 2 hour lecture
1x 1 hour tutorial

Assessment:
10% - Individual homework assignment / test. It was basically 14 multiple choice questions we could do in our own time, and later submit online.
10% - Weekly tutorial participation. Tutorial questions were due each week, you needed to make a reasonable attempt on at least 8 out of 10 in order to get the full 10% (don't have to get them right)
20% - 1 hour mid-semester exam, mid-semester (20%)
60% - 2 hour end-of-semester exam Hurdle, have to pass this exam

Lectopia Enabled:  Yes, with screen capture

Past exams available:  No, 2 sample exams were provided

Textbook Recommendation: 
"Required text"
Berk, J. and DeMarzo, P., Corporate Finance: The Core, 4th ed., Pearson Global Edition, 2017.
I bought it but rarely used it. There are pre readings but the lectures are usually enough to get by

Lecturer(s):
Asjeet Lamba

Year & Semester of completion: 2017 Semester 1

Rating: 4 Out of 5

Your Mark/Grade: High H1

Comments:
This subject was good overall. It was a very common breadth, especially for the science students (like me). It didn't assume any knowledge and was an interesting and useful breadth

Lectures:
There was a 2 hour lecture every week. The first hour was good, there was a short 5 minute break halfway through (not long enough) and then the second hour commenced. The second hour was often confusing as you were often tired and had only just learned the relevant content without enough time to go over it or understand it. Asjeet was a good lecturer, and showed us relevant (and interesting) examples of actual companies and how their share value changed, etc. He did sometimes go through the content a bit fast, but this was likely due to the time constraints and the fact that the second lecture was immediately after the first. I believe if the lecture times were further apart, it would have been a good pace.
The lecture slides were well organised, with a summary at the end and the relevant formulas (both really useful). The examples / case studies had "Case study 1: Name" written at the top of the slide, and the content had titles at the top of slides, making it easy to go through notes. The lectures were good but could have been improved by being further apart. I know lots of people stopped attending partway through semester, and this could be a good solution so that you can have a break between the lectures, but make sure you don't fall behind.

Tutorials:
My tutorial wasn't the best, although I'm sure other tutors were far better. We got into groups of 3-4 at the start to talk about one of the true/false questions for about 10min. The rest was our tutor solving the questions, sometimes trying to get an answer from us. He wasn't very engaging and I didn't learn much from the tutes, which contributed to how I found it difficult to understand some concepts, having to spend time going over concepts right before exams (I didn't have much time during the semester).

The Online Assignment:
The online assignment worth 10% was basically a take home MC test. If you put in the extra time to check your work, it was easy-ish to full-mark, just make sure you submit it on time! It covered content from weeks 1-4 and was fairly straightforward.

The Mid Semester Exam:
This covered weeks 1-5 of the subject, and was worth 20%. It had 14 multiple choice questions and was done in an hour. Most of the questions were straightforward but a couple relied on you remembering what they talked about in lectures, not necessarily just the application of formulas etc (one question in particular). If you study it should be pretty easy to do reasonably well. The time is more than enough to do most questions, with the extra time for those questions where you're struggling to get the answer out.

Final Exam:
This is a hurdle and worth 60% of your final mark. The questions often tested multiple concepts at once (eg finding a NPV of something where you're given the nominal cost, inflation rate and required rate of return or WACC). One question (10 out of 100 marks) required you to remember a graph and the names of the labels etc which I think everyone struggled with which is why they increased the exam mark by 6 marks. The multiple choice section is easy / straightforward, but to do well in the SA section you need to know the content quite well, as not knowing all aspects will cause great difficulty as most questions assess multiple things at once. There was enough time to do the exam, and it was pretty fair.

Overall
Overall this subject was a good introduction to finance. The time commitment wasn't very large (something I was grateful for) but did require time outside of lectures and tutes to understand concepts and complete the relevant tutorial questions. The 4 instead of 5 /5 was due to the long lectures and difficulty absorbing so much information at once, and the not-so-great tutes. The rest of this subject was, however, interesting and useful. I would recommend doing this subject, especially if you want to learn something practical and that you can apply to regular (financial) life.
Completed VCE 2016
2015: Biology
2016: Methods | Physics | Chemistry | Specialist Maths | Literature
ATAR : 97.90
2017: BSci (Maths and Engineering) at MelbUni
Feel free to pm me if you have any questions!

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Re: University of Melbourne - Subject Reviews & Ratings
« Reply #643 on: July 25, 2017, 12:34:28 pm »
+4
Subject Code/Name: ENGR10004 Engineering Systems Design 1

Workload:
3x 1 hour lectures (two streams)
1x 3 hour workshop

Assessment:
*5% - Mid Semester Test
*5% - Reflective journal weekly submission and marking (full marks if you do it)
*10% - Reflective journal final submission
5% - Team contract (at start)
10% - In-workshop presentation (based on final report / big project but this is done partway through)
5% - Draft report for big project
35% - Final report for big project
*25% - Final exam, 2 hours

* The individual assessments (indicated by *) form a combined hurdle

Basically, a lot of assessments

Lectopia Enabled:  Yes, with screen capture

Past exams available:  2 Past exams, only part B on the exam is provided, no solutions.

Textbook Recommendation: No textbook required

Lecturer(s):
Gavin Buskes (first half, aerospace engineering, tanks/pipes)
Ray Dagastine (second half, chemical engineering)

Year & Semester of completion: 2017 Semester 1

Rating: 3-4 Out of 5

Your Mark/Grade: High H1

Comments:
This subject heavily relied on group work, the group work making up 55% of your final mark! I rate this subject as 4 due to being lucky enough to have a dedicated group, but could easily have been 3 without them. There were very few requirements to get into this subject and so there were a lot of different kinds of people.

Content / Lectures:
The first half of the subject was usually straightforward but boring. It had some difficult application-style questions (engineering bernoulli equation was annoying). I'd call this half of the subject confusing rather than difficult, and it felt like a lot of it was spent not learning anything
The second half of this subject was taught by Ray, and it felt like a lot of things were just thrown at us, and he assumed we knew more than we did. We had integrals and a lot of various equations thrown at us without enough time to understand them. This area was particularly difficult for those not strong in maths, and even for those strong in maths it was difficult to keep up. For this half, you really need to put in the extra time to understand what's going on

Individual Assessments:
The weekly submission of the reflective journal took time (1-2 hours per week or so, depending on effort you put in and how fast you are at writing) but was an easy 5%.
The final submission of the reflective journal shouldn't take too long (maybe 3 hours or so to do referencing and looking over it), provided you've done the weekly submissions. This is worth 10% and it should be relatively easy to get 80%+ if you put in the time.
The mid sem test was short (25m) and not worth much, but was also confusing and tested a lot of random things that you don't use much, eg a MATLAB function we used once. You should be able to pass this but it's hard getting 80%+ as it really just chooses questions from random parts of the course without much of a focus on using concepts you've been taught. It's only worth 5% though so it's alright.
Having these individual assessments was a hassle but put a lot of the pressure off the exam, as it's a combined hurdle. If you put in the work throughout the semester, you shouldn't have to do too well to pass the subject and hurdle.

Group Assessments:
55% of your final mark is made up from group work, so it's essential to find a good group. There are a few "peer assessments" throughout the semester so, while your assignments are graded as a whole, your individual marks can be adjusted depending on how your peers rate you. While this system is flawed, it does encourage everyone to put in effort.
The big final report and associated assessments require a lot of time and work. My group had a 2 hour meeting and a 4 hour meeting weekly on top of the 3 hour workshops, we worked hard and got ~87%. You need a good team that's willing to put in the work and if they aren't, you'll struggle with the assessments and getting the marks your want.

Exam:
While past exams are provided, only part of them are and no solutions are given which makes it really hard to prepare. However, the past exams are very similar to the actual exam so it's understandable, just annoying. The final exam is much better than the mid semester test. The multiple choice questions are pretty straightforward , and the SA questions usually test content you've learned so do some practice questions and you should be alright (the MATLAB question/s is annoying though as you have to write out code when they don't clearly specify what they want). The exam is only worth 25% so it means you don't have to stress over this exam as much as the others and it's not the end of the world if you don't do well.

This subject wasn't amazing and relied a lot on who your team members were. The workload was very high (14 hours per week excluding travel time and  study time for me) however, the continual assessments took a lot of the pressure off the final exam which allowed me to focus on other subjects during that time period. Ultimately, I feel like I didn't learn too much but it did give me some minor skills that I expect will help in ESD 2 (eg MATLAB skills). It's a pretty mediocre subject, taught alright, not great, lots of time but not too difficult. If you're interested in engineering it's probably best you do both this subject (ESD1) and ESD2 but other subjects will probably be more interesting.
« Last Edit: July 25, 2017, 12:53:43 pm by Shadowxo »
Completed VCE 2016
2015: Biology
2016: Methods | Physics | Chemistry | Specialist Maths | Literature
ATAR : 97.90
2017: BSci (Maths and Engineering) at MelbUni
Feel free to pm me if you have any questions!

dankfrank420

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Re: University of Melbourne - Subject Reviews & Ratings
« Reply #644 on: November 05, 2017, 05:44:58 pm »
+5
Subject Code/Name: Investments - FNCE30001 

Workload:  1 x 2hr lecture per week, 1 x 1hr tute per week

Assessment: 
Weekly “assignments”: 10%
Mid-semester test: 20%
Exam: 70%

Lectopia Enabled:  Yes, with screen capture

Past exams available: 2 exams from 2009 – beyond that nothing useful.

Textbook Recommendation:  I dunno, didn’t bother to buy it. Lecture slides will suffice

Lecturer: Rob Brown

Year & Semester of completion: 2017 Sem 2

Rating: 3 Out of 5

Your Mark/Grade: H1

Comments:

Content:

The subject is split into two halves: equity and debt.

You start off with measures of return and risk, constructing optimal portfolios, the CAPM, Single Index and APT models and finally evaluating equity portfolio performance. I can see why second year statistics is a pre-req for this subject, as there is a lot of calculations involving standard-deviations, variances, covariances and correlation measures between assets. However, if you managed to get through Intro Econometrics or QM2 then the stats here shouldn’t be too bad. Nothing here was mathematically too hard, but the difficulty comes from the theory behind the models. If you’re aiming for a h1, then I’d probably advise you to be attentive in lectures and understand the derivations of the formulas/theories, but if you’re just looking to scrape through then roughly knowing your way around the formula sheet should be enough for equity.

After equity, the subject moves into debt securities – zero-coupon bonds, coupon bonds, term-structure of interest rates, portfolio performance and floating rate notes. There wasn’t as much statistics here, just seemed to be a lot of computation. Basically, this half of the course was about calculating present values of future cashflows and rates of return over a bonds life-time.

You don’t need to be a math whiz in this half of the course, in fact they take most of the math out on purpose. For example, one lecture they showed us a Taylor Expansion as part of a proof for 20 minutes, but then said “don’t worry about it” and pointed us to a derivative formula on the formula sheet and told us to not worry about where it came from.

tldr; don’t worry about the maths. It’s computational instead of being conceptually hard.

Rob Brown is a decent lecturer, but he speaks veeerrrrryyyy slowly. I stopped attending after about week 4 and listened to the lectures on 1.5x speed so it sounded normal. Some of the lectures can be a bit dry at times, but what was very useful is that he goes through worked examples of questions in the lecture itself so that was invaluable come exam time.

Mid-Semester Test:

Oh boy, this was tough - the average was 55% and no one in an enormous cohort (enough to fill 2 Copland Theatres) managed to full mark it. A friend also said that his tutor said that it was the hardest Mid-Sem he'd ever seen.
My tutor also did mention that Rob was renowned for hard exams at the start of the semester, and she was spot on. The mid-semester honestly felt like it should have been from a stats subject. There was so much manual computation of variances and covariances and correlations, everyone was shocked by it. There were no free mark questions, everything was either a long and arduous computation or specific theory questions. There was also a tonne of those “which of the following statements are true” questions, but you could go through the formula sheet and knock a few of the obvious ones out. I think people were fooled by the deceptively easy lecture slides and tutorial questions, because the Mid-Sem was a clear step up from what was covered in class. A lack of revision material didn’t help things either.

Assignments:

These just consisted of handing a few part B tutorial questions up. Calling them “assignments” is insulting to actual assignments, as these could be smashed out in 30 minutes easily. You don’t even have to get them right – just showing an attempt at trying to get the answer is enough to get 10/10 for the semester.

Exam:

The exam was somewhat tricky I found. 9 MCQs worth 3 marks each, then a bunch of short answer questions. The exam focuses more on the second half of the course, which was good. However, there weren’t any free marks asking you to do simple stuff like identifying which formula to use and just subbing numbers in there. There were many long, arduous computational questions (Treynor-Black Method is a pain in the ass) and a lot of theory – I’d say about a 50/50 split between theory and maths.

My advice for the exam?

-   Know your way around the formula sheet. This is super helpful for MCQ where you can just plug numbers in and return one of the options on provided even if you don’t know what you’re doing. This happened to me a number of times – just trial and error with the formula sheet can go a long way with MCQ.
-   Try to develop an intuitive understanding of the theory, instead of just rote learning. For example, it’s easy to write down in your book “Yield curve for upward sloping zero rates is below the zero rate curve”, but if you know the ins-and-outs of why the yield curve is the way it is then you’ll nail any question on the exam. Developing a mathematical intuition behind all the theory makes it super easy to apply come exam time.
-   Learn how to take advantage of arbitrage situations. This isn’t really “taught” well in the course, you must develop your own method of doing it. But if you forget everything else – go long on the under-priced asset, short the other stuff. There is usually a ~10 marker on arbitrage so if you learn it you’ll be put in a good place for high marks.

Overall Investments wasn’t really too hard a subject for a level 3 finance, the mathematical rigor is pretty basic – its just looking and seeing which formula from the sheet you need to apply and which methodical/computational process you have to churn through. The difficulty comes from the theory, but if you make an effort to understand why things are the way they are instead of just accepting them at face value, you’ll be in a good place come exam time. The subject content is pretty dry as well, although I suppose if you're interested in finance enough to major in it then you'll find it somewhat interesting.

Good luck :)
« Last Edit: November 22, 2017, 10:47:24 pm by dankfrank420 »