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March 29, 2024, 01:13:34 am

Author Topic: Psychology 2014  (Read 71330 times)  Share 

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shadows

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Re: Psychology 2014
« Reply #15 on: December 16, 2013, 11:59:24 pm »
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Hey 2014'ers, looking forward to psych next year! Are any of you doing AOS1 in the holidays? How do you plan to make notes for psych (linear, mind maps etc)?

Yeah I plan on getting through AOS1 on the holidays.
Not sure on the note taking, I think I'll try mind maps etc but I've always worked well with normal summarising. What good methods have you stuck with that work from last year?

 Because psychology is something I actually enjoy, I really would like to just read it (just for fun) and get a broad overview of psych before the school begins. Then learn AOS1 properly.

Do you reckon doing the questions in the textbook would be a good idea. Would it be time well spent, or would there be better more worthwhile things to do.

Paulrus

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Re: Psychology 2014
« Reply #16 on: December 17, 2013, 12:33:48 am »
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Do you reckon doing the questions in the textbook would be a good idea. Would it be time well spent, or would there be better more worthwhile things to do.
if the new edition of the textbook is anything like the old one, the textbook questions are pretty useless. i'd only bother with them if your teacher sets them as classwork.

if you guys need any help/emotional support during next year, feel free to shoot me a message any time  :)
good luck for next year!
2015-2017: Bachelor of Arts (Psychology) at University of Melbourne.

shadows

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Re: Psychology 2014
« Reply #17 on: December 17, 2013, 01:02:24 am »
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if the new edition of the textbook is anything like the old one, the textbook questions are pretty useless. i'd only bother with them if your teacher sets them as classwork.

if you guys need any help/emotional support during next year, feel free to shoot me a message any time  :)
good luck for next year!

which textbook did you think the questions were pretty useless for?
I have both the macmillan and the oxford one (although oxford is the one prescribed by school)

Paulrus

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Re: Psychology 2014
« Reply #18 on: December 17, 2013, 02:13:50 am »
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i was using the grivas (macmillan) textbook. the questions were mostly just basic reading comprehension stuff which are meant to consolidate what you've learned, but i found a lot of them were pretty irrelevant to what's on the study design. they could come in handy if you're struggling to understand a particular concept though

also remember to have a copy of the study design handy when you're going through chapters, there's a lot of information in there that you don't need to know, and you don't want to be memorising anything you don't need.
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xlaiyn

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Re: Psychology 2014
« Reply #19 on: December 17, 2013, 11:42:29 am »
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Since I'm picking up Psych next year, I've heard the one thing you want to definitely make yourself familiar with is research methods. I ordered a research methods workbook and it came yesterday. It seems incredibly helpful. Has anyone else heard of it so far?

VCE Psychology Research Methods Workbook, 1st Edition
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LastOfUs

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Re: Psychology 2014
« Reply #20 on: December 17, 2013, 09:39:59 pm »
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Since I'm picking up Psych next year, I've heard the one thing you want to definitely make yourself familiar with is research methods. I ordered a research methods workbook and it came yesterday. It seems incredibly helpful. Has anyone else heard of it so far?

VCE Psychology Research Methods Workbook, 1st Edition
- Kristy Kendall

Nope.

Recommend picking it up?
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xlaiyn

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Re: Psychology 2014
« Reply #21 on: December 17, 2013, 09:53:10 pm »
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Nope.

Recommend picking it up?

It seems fairly useful so far, and it was apparently written by a teacher of VCE psychology. I've worked through the first few examples, and they basically explain the processes that a psychologist goes through in order to correctly answer a research question. I'm pretty happy with it, and at the back it also has a somewhat extensive glossary with terms used in the research methodologies section of the study design and the course. It isn't too expensive, either, so I'm going to hope that it helps me bridge the gap I have after not taking the 1/2, haha.
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LastOfUs

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Re: Psychology 2014
« Reply #22 on: December 17, 2013, 09:55:04 pm »
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It seems fairly useful so far, and it was apparently written by a teacher of VCE psychology. I've worked through the first few examples, and they basically explain the processes that a psychologist goes through in order to correctly answer a research question. I'm pretty happy with it, and at the back it also has a somewhat extensive glossary with terms used in the research methodologies section of the study design and the course. It isn't too expensive, either, so I'm going to hope that it helps me bridge the gap I have after not taking the 1/2, haha.

I took the 1/2 but can't remember anything to do with research methods! I'll pick it up, thanks.
My VCE 2014 Goal is to not end consciousness ... and a respectable ATAR.

totaled

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Re: Psychology 2014
« Reply #23 on: December 17, 2013, 10:22:44 pm »
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Just some research methods notes that I found that I had from a few years ago :)
Not sure if it's completely relevant now or not, but hope it helps


RESEARCH METHODS NOTES:
Formation of Operational Hypothesis –> IPOD – IV, population, operational (DV), DV -> use the phrase 'AS OPERATIONALISED BY...'
Research hypothesis – a testable statement predicting the outcome of research study
Hypothesis – tentative and testable prediction of the relationship between two or more events/characteristics
-> An educated guess of what the researcher thinks the results will be
Operational definitions define an observable event in terms of the procedures used to measure that event

Operational Hypothesis/research hypothesis – a hypothesis which states how the variables being studied will be observed, manipulated and measured, and outlines the population from which the sample has been selected
-> ‘Operationalised’ – defined in terms of the procedures used to measure the relevant concepts. The definition should enable one to know exactly what concept is being measured in an experience and how it is measured.
•   Using ‘As Operationalised’ is often a good way to ensure you mention how the DV is measured.
Example: clinically depressed adult males and females who walk at 3km per hour for thirty minutes daily over a period of five days will use fewer negative words when writing a creative story than those clinically depressed people who do not walk each day.

Research design methods – used to minimise effects of extraneous variables

Repeated Measures Design – each participant is involved in both the experimental and control conditions of an experiment.

ADVANTAGES –
-   Interpersonal variables can be controlled by this design by controlling participant variables
-   Eliminates the effects of participant variables
-   Fewer subjects required compared to independent groups
DISADVANTAGES –
-   Order effects -> learning/boredom may interfere with results
-   More time will be needed
Order Effect/Practise Effect – the sequences in which the conditions were performed may become an extraneous variable as performance in the task completed second may be better because of the experience gained in completing the first task, and not because of the ______.

Boredom Effect – participants may be fatigued/bored when they come to complete the second task and not perform as well.

Counterbalancing – involves arranging the order in which the conditions of a repeated measure design are experienced so that each condition occurs equally often in each position. -> Usually ensures order effect balanced out, although there are no guarantees.

Matched Participants Design – involves the selection of pairs of participants who are very similar in a characteristic (s) that can influence the DV, then allocating each member of the pair to different groups.

ADVANTAGES –
-   No order effects, eliminating the need for counter balancing
-   The effects of the variable on which participants were matched (say what it is) have been eliminated as a possible confound.
DISADVANTAGES –
-   The design is very consuming and perfectly matching participants can be difficult to achieve.

Independent Groups Design – each participant is randomly allocated to one of two (or more) entirely separate (‘independent’) groups.

ADVANTAGES –
-   Likely to result in two groups that are evenly matched, but less likely in smaller groups
-   No order effects to control
DISADVANTAGES –
-   Needs more participants for same strength of results
-   Participant variables such as gender and literacy skills are not controlled.
Experiment Information -> used to test cause-effect relationship between variables.

What makes a study an experiment?
-   Being able to test a hypothesis under controlled conditions to explore the effect of the IV on the DV.
-   The levels of the IV are directly manipulated/controlled by the investigator.
-   There is a control and experimental group.

Random Sampling – ensures every member of the population of research interest has an equal chance of being selected as a participant for a study (e.g. lottery method)

Stratified Sampling – involves dividing the population to be sampled into distinct subgroups, or ‘strata’, then selecting a separate sample from each stratum, in the same proportions as they occur in the target population.

Random Allocation – participants selected from the experiment are as likely to be in one group as the other

Placebo Effect – occurs when there is a change in the response of participants due to the belief that they are receiving some kind of experimental treatment, as opposed to the change occurring due to the specific procedure (that is, the experimental treatment) e.g. smoking while car driving.

Experimenter effect – change in participant’s response due to the experimenter’s actions rather than to the effect of the independent variable (experimental treatment).
E.g. self-fulfilling prophecy: participants behave how they believe the experimenter expects them to behave e.g. facial expressions, smiling, mannerisms, and tone of voice.

Experimenter Bias – when the person measuring the dependant variable is aware of the purpose/hypothesis of the experiment, it is possible that they can misread data, misinterpret verbal responses, and give unintentional assistance to participants.
=> For the above terms, and blind procedures, often refer to Bias/Expectations.

Independent Variable – a condition that an experimenter systematically manipulates, changes or varies in order to gauge its effect on another variable.

Dependant Variable – in an experiment it is the condition that is affected by changes or variations in the IV.

Extraneous Variable – any variable other than the independent variable that has the potential to influence the dependant variable and therefore affect the results of the experiment in an unwanted way

Confounding Variable - when the uncontrolled variable is confused, or confounded, with those of the independent variable, the uncontrolled variable is referred to as a confounding variable.


Ethical Considerations

NHRMC – Code of ethics -> standards that guide individuals to identify good, describable and acceptable conduct.
-   To protect rights and welfares of participants (no harm)
-   Promote research to benefit mankind (maximising beneficence)
Integrity is demonstrated by a commitment in research to the search for knowledge. Honest and ethical conduct in research including the disclosure and communication of results obtained from research.
-> Is the researcher demonstrating a genuine commitment to the research?

Respect for persons is demonstrated when the researcher properly regards the welfare, rights, beliefs, perceptions, customs and cultural heritage of all individuals involved in research.
-> How is the research designed to ensure that the participant is respected and their dignity maintained?

Beneficence refers to the researcher’s responsibility to maximise possible benefits and minimise risks of harm or discomfort to all research participants. Participant’s dignity, well-being is of a higher priority than expected benefits of knowledge.
-> Do the potential benefits for the research justify the risk to the participant?

Justice is demonstrated by researchers ensuring that there is a fair distribution of benefits and burdens within a population of research interest, as well as for any individual research participant.
-> Is the participant representative of other participants intended to benefit from the research findings? Participants have a right to fair treatment.

Australian Psychology Society Guidelines – CIV DD W
The welfare of the participant must be of upmost importance

UNDERLYING GUIDELINE -> no physical or psychological harm to the participant should occur as a result of the participant’s involvement in the research.

Confidentiality – participants have the right to privacy, so any details of their involvement in a study cannot be revealed in a manner that enables individuals to be identified, unless their written consent is obtained. This includes the storage and disposal of information, as well as access of research data.

Voluntary participation - involves the researcher ensuring that participant’s involvement in the research is voluntary. Participants must not be placed under pressure to take part in a study.

Informed consent procedures – participants must be informed of the nature and purpose of the investigation as well as any possible harm. Legally incapable – must obtain participant’s consent and obtain appropriate consent from those legally responsible. An Ethics Committee is needed if deciding that research does not require written consent from research participants.

Withdrawal rights – inform the participants of the nature of research and they are free to participate or to decline to participant or to withdraw from research at any time, even without reason.

Deception in research – researchers must ensure that participants do not suffer from distress from the research procedure. All cases involving deception, participants must be debriefed at the conclusion of the study.

Debriefing – provide an opportunity for participants to obtain appropriate information about nature, results and conclusions of the research 
-   Correct mistaken attitudes and beliefs about the research
-   Anticipate subsequent effects of research participation and provide information on services available to alleviate stress.
-   Full explanation of the findings in this study.

-> AIM: to ensure participants leave in as similar state as they did entering it.

Statistical Analysis; (including inferential and descriptive statistics)

Descriptive Statistics – are used for analysing, organising, summarising and describing the important features of data so they can be more easily interpreted and communicated.  -> The specific type of descriptive statistic used usually depends on the kind of research done and type of data collected.
E.g. plotting a graph, calculating a mean mark for test scores, are examples of descriptive statistics.

Measures of central tendency -> the single numerical score that can describe the whole group. This indicates a ‘centre’ or ‘average’ value in a set of scores. The main three: mean, mode, median.  -> The mean is preferred, as it makes use of every individual score and can be used in more advanced statistical analysis.
Measures of variability: range, interquartile range, variance, and standard deviation.
-   Mean – arithmetic average, which can be useful if scores in a set of data cluster closely around a central score, but not useful if extreme scores exist, as this can be unreliable.
-> The MEAN is the most sensitive measure of central tendency.
-   Median – middle score (middle point) of a set of scores, useful when many extreme scores exist, not useful when large amount of data (time consuming and impractical)
-> I.e. half scores above or equal to middle, the other half, below or equal to.
-   Mode – the most frequently occurring score. A single score can alter the mode dramatically. It is a useful indicator of the ‘common/usual’ score, because it shows the most occurring (typical) score.

Frequency Distribution - is a way of organising data to show how often (frequent) a value/measure occurs in a set of data. Can be represented in table/graph
Graphs – used to provide a pictorial representation of the results of a study. Usually the frequency is on y-axis, unit of measurement (score, time) on x-axis

-   Line-graph: commonly used to indicate the relationship between two factors, or two variables in an experiment. Important feature: variable plotted as the x-axis is continuous
-   Bar graph: shows how frequently a category of data occurs by representing the data using a series of discrete (separate) bars or rectangles next to, but not touching one another. X-axis usually shows type of categories. Categories on x-axis are distinct (not continuous)
Sometimes used to represent values from the columns (i.e. percentage bar graph)
-   Histogram – show frequency with which a particular score occurs in a set of data. Bars are drawn so they touch each other. Indicates that the original variable is quantative (numerical).
-   Frequency polygon – used to graph the frequency of data, but presentation like bar graph.
-   Pie graph – pie chart is a circular diagram that shows the proportions of scores, values or

Inferential statistics - a type of statistics used to make judgements about whether the results for a sample would also occur in the population from which the sample was drawn. Also used to enable the research to determine the statistical significance (this is the primary purpose) of their results (how likely it is that results obtained occurred by chance) use mathematics to draw conclusions from the results of a study (to compare the sample to the population).
-> Unlike descriptive statistics, they enable researchers to draw inferences, or conclusions based on evidence, about the results obtained in a study.

P value is a probability value of the significance level of any difference. Repetition is likely to reoccur if:
- undertaken in an area likely to be immense benefit to society or
- involves a treatment that could have some chance of harm
-> The actual p value for results is established before the experiment is conducted.
-> Generally accepted for 0.05. If the p value ≥ 0.05, e.g. a significance level of p ≤ 0.06, means the difference in mean scores obtained was most likely due to chance and this would be unacceptable. It would therefore be said that the results did not support the hypothesis and a conclusion would be made that this difference obtained was most likely due to chance alone.
Example: p = 0.01, is a low value, indicating a probability of 1% that results are due to chance alone.

Statistical significance is the term used to indicate whether the difference in the results obtained for the control and experimental groups is a real difference, due to the independent variable, and probably not due to chance factors alone. In any experiment, the mean scores from each group will not be identical. If the likelihood of the difference occurring by chance is extremely low, then it is said to be statistically significant (if the p value is low, the results are considered as ‘statistically significant’)

A test of significance is therefore used to determine whether the mean scores of two groups differ significantly, that is, whether the difference is due to the independent variable and is unlikely to have occurred by chance alone. One of the most commonly used tests of significance is called the t-test.

T-test is a mathematical procedure that involves a comparison of the means of two groups.  Using a t-test to compare the means would provide a t value (a number) that is checked against a set of p values that indicate how likely it is that the difference is due to chance. [Anova also possible] A t-test can be used:
-   -  When only two conditions are being compared (e.g. presence/absence of independent variable)
-   - To compare means of samples (e.g. groups) drawn from populations but not comparing means between entire populations.
-   - If the distribution scores for each group (spread of individual scores around the mean) are similar and normally distributed (i.e. normal, bell-shaped curve)

Limitations –
-   No more than 2 conditions/levels of an independent variable can be compared.
-   Cannot be used if scores on variables are not normally distributed around the mean, that is, they cannot be used wit ha skewed distribution of scores.

A conclusion is a decision made by the researcher about whether the hypothesis was supported or rejected based on the results obtained in the experiment.
One conclusion: whether the hypothesis is supported/rejected on the basis of results obtained. Requires objective/unbiased judgement, as results may be influenced (e.g. extraneous variable) as the researcher must be confident that any change to the dependent variable was due to the independent variable and not other variables
-> In science, a hypothesis can be supported or rejected, but it cannot be ‘proven’ true.

The other conclusion is known as a generalisation. A generalisation is a decision/judgement about how widely the findings of a study can be applied, particularly to other members of the population from which the sample was drawn. Make sure uncontrolled variables accounted for, and that results between Iv and DV are statistically significant.
-> Generalising the results from the sample to the population is risky if the sample is not representative of the population of interest. It is reasonable to assume if: relationship between the independent variable and dependant variable is strong, and the sample of participants is not particularly unusual.

Collection and interpretation of data

Data is collected objectively through observation, questionnaires, surveys, interviews, tests or physiological recordings. Collection involves raw data and is not processed. An interpretation of data must also be free of bias. It can be done through organising and representing the data in a meaningful way (e.g. through graphs, the median, mode, mean or standard deviation). This is so that the experimenter can judge as to whether or not the hypothesis has been supported.

Reporting of findings and conclusions

A conclusion is an objective decision about what the results obtained from the research investigation mean. It is made in the “discussion” section of a report. It states whether or not the hypothesis was supported, mentions extraneous variables and limitations, and makes applicable generalisations of results if such generalisations are reasonable.

EXPERIMENT NOTES
An experiment is used to find out if there is a cause-effect relationship between behaviours/events of interest.

How is the study an experiment?
-   It testes a hypothesis under controlled conditions to explore the effect of an independent variable on a dependant variable.

Sampling: the process of selecting participants for research.
Sample: a group that is a subset of a larger group chosen to be studied for research purposes.
Done so participants in sample can be used to make inferences on population

Population: the larger group from which a sample is drawn. A sample should be representative of the entire population of interest. So you can GENERALISE from your results.

•   Random Sampling is a sampling procedure that ensures that every members of the population of research has an equal chance of being selected as a participant for the study. I.e. Selection of one participant does not influence selection of another

Biased sample – the opposite, not everyone has an equal chance.

•   Stratified sampling: divides the population of interest into particular strata (groups) and then selects a sample at random from each stratum in the same properties as they exist in the population.
   Sample can be assumed to be truly representative and unbiased.

Experimental group: is exposed to the independent variable which is the condition that receives the ‘treatment’

If large enough change in DV, you can conclude likely cause of IV and not some other factor.

Control group: A control group is one that is not affected by the independent variable, and is often used to determine if any change made was purely due to the influence of the independent variable, that is, to act as a baseline.

Random allocation: participants selected for the experiment are as likely to be put in one group as the other. With larger number of participants, reasonable to assume each group will contain about equal numbers of characteristics that can affect the results.

Placebo is a neutral or inactive substance given to the control group. This inert ‘treatment’ is used to equalise the expectations of the control group and experimental group.

Placebo Effect: occurs when there is a change in the response of participants due to the belief that they are receiving some kind of experimental treatment, as opposed to the change occurring due to the specific procedure (experimental treatment) that is used to produce the response.

Hawthorn Effect: performance may improve simply because of the fact that they are aware that they are members of an experimental effect.

Single-blind Procedure: either participants or the experimenter do not know whether the participants are in the control group or experimental group condition. Prevents participant’s knowledge or expectations of the experiment impacting results

Experimenter Effect – occurs when there is a change in the participant’s response due to the experimenter’s actions rather than to the effect of the independent variable.

Examples –
•   Self-fulfilling Prophecy - tendency of participants to behave in accordance with how they believe an experimenter expects them to behave e.g. facial expressions, mannerisms, tone of voice.
•   Experimenter bias – unintentional biases in collection of data - A person measuring DV is aware of purpose/hypothesis of experiment. IT is possible for them to misread data, misinterpret responses, or give unintentional assistance to participants.

Double blind procedure - neither the participant nor the experimenter are aware of the conditions to which the participants have been allocated. In experimenters where knowledge of conditions may affect behaviour of experimenter as well as the participants

An extraneous variable is any variable other than the independent variable that can cause a change in the dependant variable and therefore affect the results of the experience in an unwanted way.

When the effects of an uncontrolled variable are confused, or confounded, with those of the independent variable, the uncontrolled variable is referred to as a confounding variable.

RESEARCH DESIGNS: the allocation of participants to minimise participant related extraneous variables

Repeated measures design: each participant involved in both the experimental and control conditions of an experiment so that the effects of individual differences between participants’ characteristics balance out exactly.

•   Negative: potential extraneous variable: ‘order effect’
   Gain experience, or boredom/fatigue, can confuse results.

COUNTERBALANCING: arranging the order in which conditions of a repeated measures design are experienced so that each condition occurs equally often in each position.

   Usually ensure order effect is balanced out, although there are no guarantees.

Matched participants design: selection of pairs of participants who are very similar in a characteristic(s) that can influence the dependant variable, then allocating each member of the pair to different groups

•   Positive: eliminates participant related variables FOR THE FACTORS WHICH THEY HAVE BEEN MA TCHED UPON.

•   Negative: this design is very time consuming and perfectly matching participants can be difficult to achieve.

Independent groups design: each participant is randomly allocated to one of the two (or more) entirely separate groups. => Known as a between-subject design.
One control, one experimental in simplest form
*Likely to result in two groups that are evenly matched, but less likely in smaller groups.

Negative:  Interpersonal VARIABLES BETWEEN PARTICIPANTS COULD AFFECT RESULTS. NOT INTRA.


Operational Definitions: define an observable event in terms of the procedures used to measure the event
Hypothesis: a tentative and testable prediction of the relationship between two or more events or characteristics
-> It is based on careful observations or theory or evidence or evidence (i.e. is ‘educated’.
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xlaiyn

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Re: Psychology 2014
« Reply #24 on: December 17, 2013, 10:34:12 pm »
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Holy crap, thank you, totaled!
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xlaiyn

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Re: Psychology 2014
« Reply #25 on: December 17, 2013, 10:48:43 pm »
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I did Psych this year and got a 46 for it as a year 11. I still have my study notes on my computer, would anyone be interested in them?

Definitely!
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LastOfUs

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Re: Psychology 2014
« Reply #26 on: December 18, 2013, 12:48:32 am »
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I did Psych this year and got a 46 for it as a year 11. I still have my study notes on my computer, would anyone be interested in them?
YES PLEASE!!!
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ealam2

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Re: Psychology 2014
« Reply #27 on: December 20, 2013, 11:02:27 am »
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I did Psych this year and got a 46 for it as a year 11. I still have my study notes on my computer, would anyone be interested in them?

Yes please, thank you very much!  :)

shadows

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Re: Psychology 2014
« Reply #28 on: December 21, 2013, 12:09:40 am »
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ASO1 includes chapters 1-5 for grivas right? I'm not sure if there are other chapters needed for ASO1.


xlaiyn

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Re: Psychology 2014
« Reply #29 on: December 22, 2013, 09:13:40 am »
+1
ASO1 includes chapters 1-5 for grivas right? I'm not sure if there are other chapters needed for ASO1.

I'm fairly certain, yes. I took a quick look at the study design and it includes content covered in those chapters.
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