7146157914555This document describes how to complete the Research Report, which is worth 25% of your final grade in PSYC1040. The report is due by 4

7146157914555This document describes how to complete the Research Report, which is worth 25% of your final grade in PSYC1040. The report is due by 4pm on 17th May and must be submitted via TurnItIn.

All tables and figures in your report must be made by you. When writing the report, please follow closely the formatting rules as set out in the 7th Edition of the American Psychological Association (APA) Publication Manual: https://apastyle.apa.org/style-grammar-guidelines00This document describes how to complete the Research Report, which is worth 25% of your final grade in PSYC1040. The report is due by 4pm on 17th May and must be submitted via TurnItIn.

All tables and figures in your report must be made by you. When writing the report, please follow closely the formatting rules as set out in the 7th Edition of the American Psychological Association (APA) Publication Manual: https://apastyle.apa.org/style-grammar-guidelines7789331921932PSYC 1040

Psychology Research Methodology 1

2024 - Semester 1

Report Instructions

00PSYC 1040

Psychology Research Methodology 1

2024 - Semester 1

Report Instructions

Overview

A primary goal of this assessment is for you to conduct a set of correlation analyses, as explained in detail in the following pages, based on the data that were collected in tutorials in week 2. You will choose 3 hypotheses to test. These hypotheses will determine which correlation analyses you run, and what you will focus on in each section of the report.

You must write a research report that summarises the study. Your report will include the following sections:

Abstract

Introduction

Methods

Results

Discussion

Appendices

The study was run in the tutorials of Week 2, Semester 1, 2024. The final dataset came from 112 participants, consisting of first year psychology students from PSYC1040. Participation in the experiment was voluntary but students were encouraged to participate to better prepare for writing their research report.

Some things to note before you read on:

Although this document is long, try not be overwhelmed: we set aside lots of tutorial time to explain each section of the report.

Correlationswhich youll need to understand for the reportare covered in Week 6, after which youll still have several weeks to work on the report before the deadline.

You can download the Report Template and use it as a guide to help you write the report.

The final page of this document is a checklist of all the things you should have completed for each section of the report.

Your Hypothesis options:

We collected data on many variables during Week 2, so there are many different hypotheses that we could test. All of the variables are explained in detail in the following pages. Below are six candidate correlations. You must choose three correlations from this list for your report:

Openness with Test and Class Anxiety

Conscientiousness with PSYC1040 Expectations

Extraversion with Fear of Teachers

Agreeableness with Worth of Statistics

Neuroticism with Interpretation Anxiety

Nerdiness with Statistics Self-Concept

After you have finished reading about the variables in the following pages, you can come back to these options and choose the three correlations you would like to perform.

For each of the three correlations you choose, you need to state a clear hypothesis about that relationship. Each hypothesis should indicate (1) which variable is the predictor (independent variable) and which is the criterion (dependent variable), and (2) the direction (sign, positive or negative) of the expected relationship. Here is an example statement using the relationship between Neuroticism and Asking-for-help Anxiety (this correlation is not one of the six you have as options; its just used as an example):

Example Neuroticism with Asking-for-help Anxiety:

The personality trait of Neuroticism reflects a persons tendency to experience negative emotions. These tendencies would be evident when asking for help with statistics. Therefore, an example hypothesis could be: I expect to find a positive correlation between Neuroticism scores and Asking-for-help Anxiety scores.

Use the above example as a guide to formulate your own hypotheses about your chosen three correlations from the above list. Your hypothesis doesnt need to be correctyou wont lose marks if your results are against your predictionbut you do need to justify why you expect your hypotheses to be true.

To choose your three correlations, and to come up with your hypotheses and justifications, consider the nature of each variable as described in the next section of this document.

Understanding each variable and the data that were collected

Data organization, exploration, and description

Raw data about each participant are in the Excel file, PSYC1040 Sem1 2024 Research Report Data. Please download this file and have a look inside.

The variables are arranged in columns in the file in the following order:

Participant identification number (Participant #)

Gender (1 = Male; 2 = Female; 3 = Non-binary/third gender; 4 = Prefer not to say)

Age (in years)

Total scores from the Big Five Personality Scale for Openness

Conscientiousness

Extroversion

Agreeableness

Neuroticism

Total Nerdy Personality Attributes Scale score

Total score from the Statistics Anxiety Rating Scale (STARS) for Test & Class Anxiety

Interpretation Anxiety

Asking-for-help Anxiety

Worth of Statistics

Fear of Statistics Teachers

Statistics Self-Concept

PSYC1040 Expectations

Understanding the Data Set

Before running any analyses, make sure you are clear about what results you expect (predict).

For a scatterplot showing a correlation, it doesnt matter which variable is plotted on which axis. However, we generally have an idea about which variable is assumed to predict or cause the other (the predictor or independent variable) and which variable is being predicted or affected (the criterion or dependent variable). By convention, the predictor variable goes on the x-axis and the criterion variable goes on the y-axis.

For this study, we can think of scores on our Big Five Personality measures and the Nerdy Personality Attributes Scale as the predictor variables. We can think of the Statistics Anxiety Rating Scale (STARS) measures and the PSYC1040 Expectations Question as the criterion variables.

Possible Values of each Variable

In the online questionnaire, each item presented a statement and invited a rating with five response options. For most variables, the questionnaire software automatically coded the responses so that lower numerical values indicate disagreement and higher numerical values indicate agreement. However, you should be careful when interpreting the numerical values because the same value sometimes has a different meaning between different variables, as described next.

The Big Five Personality Scale

This scale contains 50 items, made up of 10 items in each of five subscales (Openness, Conscientiousness, Extroversion, Agreeableness, and Neuroticism; OCEAN for short). For some items in each subscale, high scores represent a high level of the trait, while for other items high scores indicate low levels of the trait. For example, one item on the Extroversion subscale is I am the life of the party. On that item, a response of Very Accurate reflects a high level of extroversion. Another item is I have little to say. This time, a response of Very Accurate indicates a low level of extroversion. We would usually need to recode these reverse-scored items as shown in the table below.

Normally-scored items

Reverse-scored items

Very Inaccurate = 1

Moderately Inaccurate = 2

Neither Inaccurate nor Accurate = 3

Moderately Accurate = 4

Very Accurate = 5

Very Inaccurate = 5

Moderately Inaccurate = 4

Neither Inaccurate nor Accurate = 3

Moderately Accurate = 2

Very Accurate = 1

This recoding has already been performed for you. To arrive at an individual score on each of the subscales, we just sum all the values from the ten items. These totals are what appear in Columns D-H in the data file.

Roughly speaking, scores on each of the five personality measures can be interpreted as follows:

Openness to Experience (O) is the personality trait of seeking new ideas and aesthetic experiences. High scorers are curious and have artistic interests. Low scorers may be more conservative.

Conscientiousness (C) is the personality trait of being hardworking and organised. High scorers tend to (for example) follow rules and prefer clean homes. Low scorers may be untidy and less reliable.

Extroversion (E) is the personality trait of seeking fulfillment from sources outside the self or in community. High scorers tend to be very sociable while low scorers are less so.

Agreeableness (A) reflects how much individuals adjust their behaviour to suit others. High scorers are typically polite and fit in with other peoples preferences. Low scorers may be more blunt and 'tell it like it is'.

Neuroticism (N) is a tendency to experience negative emotions.

Example items:

Please rate how accurately the following statements reflects who you are:

I am quick to understand things. (Openness to Experience)

I pay attention to details. (Conscientiousness)

I am the life of the party. (Extroversion)

I am interested in other people. (Agreeableness)

I get stressed out easily. (Neuroticism)

So, what is the range of values we should expect for the personality subscales (Columns D-H)? Well, each number represents the sum of the ten responses to each subscale. Each response could take any value from 1 to 5. So, if someone responded 1 to all ten items, what would their total be? If they responded. 5 to all ten items, what would their total be? Answering these two questions tells us what the expected range of values on these scales is. Any observations outside that range would be impossible scores and they would need to be removed from the data set prior to computing the correlation.

Nerdy Personality Attributes Scale

This scale consisted of 50 items that reflect nerdy personality traits. The scale is not divided into subscales. Each item invites participants to rate how accurately a statement reflects who they are.

Example item:

Please rate how accurately the following statement reflects who you are:

I would rather read a book than go to a party.

As in the Big Five Personality Scale, some items in The Nerdy Personality Attributes Scale are reverse-scored. After automatically recoding responses appropriately, the scores in Column I of the data file represent the total of the 50 items on this scale. Again, to work out the expected range of values for this scale, ask yourself what the total score would be if a participant responded 1 or 5 to all 50 items.

Statistics Anxiety Rating Scale (STARS)

This scale has six subscales: (1) Test and Class Anxiety, (2) Interpretation Anxiety, (3) Anxiety Associated with Asking For Help, (4) Worth of Statistics, (5) Fear of Statistics Teachers, and (6) Statistics Self-concept (perceived ability to cope with maths in statistics).

Like the other two scales, each item is scored on a scale of 1 to 5. However, in the STARS, each subscale consists of a different number of items. Therefore, to work out the range of expected values, we need to take into account the number of items for each subscale individually:

Test and Class Anxiety: 8 items on this scale.

Higher values indicate greater anxiety during statistics tests and classes.

Interpretation Anxiety: 11 items.

Higher values indicate greater anxiety when interpreting statistics.

Ask-for-help Anxiety (anxiety associated with asking for help): 4 items.

Higher values indicate greater anxiety when asking for help about statistics.

Worth of Statistics: 16 items on this scale. (Warning: this is a tricky one)

Higher values indicate a more NEGATIVE attitude towards statistics.

Fear of Statistics Teachers: 5 items on this scale.

Higher values on this scale indicate greater fear of statistics teachers.

Statistics Self-concept (confidence with maths in statistics): 7 items. (Warning: this is a tricky one)

Higher values on this scale indicate LESS confidence when working through statistics calculations.

Example items:

Please rate how much anxiety you would experience in the following situations:

Walking into the room to take a statistics test (Test and Class Anxiety)

Walking into the room to take a statistics test (Interpretation Anxiety)

Asking one of your lecturers for help understanding the output of a statistics program (Asking-for-help Anxiety)

Please indicate your level of agreement with the following statements:

Statistics takes more time than it is worth (Worth of Statistics)

Most statistics teachers are not human (Fear of Statistics Teachers)

Since I never enjoyed maths I dont see how I can enjoy statistics (Stats Self-concept)

PSYC1040 Expectations

This scale had only one item. On a scale of 0-100, with 0 being completely disagree and 100 being completely agree, participants respond to the following statement:

I feel like I am going to have a positive experience and successful semester in PSYC1040.

Analysis instructions

Explanation of Data Screening

Once you have chosen the three relationships you want to evaluate (that is, once you have chosen your hypotheses), a key preliminary step is to screen the data for unusual/impossible observations. Screen your data on the relevant variables and note any impossible scores. A researcher needs to be keenly aware of the range of possible values on each measure. Data screening can involve the removal of observations because they are impossible scores, among other reasons. It is often easy to spot impossible scores if you construct a bivariate scatterplot (which you need to include in the appendices): in the scatter plot, you can visualise the cut off for impossible scores to quickly see which pieces of data need to be removed.

Steps to follow for Data Screening and Statistical Analyses

Refer to the Report Template (a separate download) for all the required graphs and computations.

Below are steps for data screening and the analyses of correlation and shared variance (remember to show the formula for correlation, the critical values, and the final answer, rounded to two decimal places in an appendix):

Step 1. Screen your data for impossible scores (if any).

Based on your knowledge of the possible responses to the variables involved in the three relationships you are evaluating, screen each variable for impossible scores. If you find an impossible score, you need to remove that participant from that specific analysis. However, be sure to keep that participant for other analyses if their other scores are within the acceptable range for the relevant variables.

Note: if you remove any impossible scores, you must recalculate the mean and standard deviation (without the impossible scores) for the relevant variable(s) in order to use the definitional formula to compute the Pearsons r.

Step 2. For your first chosen relationship

compute the linear correlation between the variables,

then compute the shared variance between the variables.

Step 3. For your second chosen relationship

compute the linear correlation between the variables,

then compute the shared variance between the variables.

Step 4. For your third chosen relationship

compute the linear correlation between the variables,

then compute the shared variance between the variables.

Step 5. Assess the direction (positive or negative) and strength of each of the three relationships.

Did the results support your hypotheses?

How strong was the support?

Writing the report what goes in each section?

Here are some guidelines for each of the sections in the order that they will appear in your report (note that you will not write them in this order). You must adhere to APA 7th Edition style and formatting practices for a research report (2% of report marks).

Title Page

A running header (a short version of your title).

Title (word limit: 40).

Your name.

Your tutors name.

Abstract (word limit: 150) (8% of report marks)

You will write the abstract.

The abstract appears by itself on a single page.

You need to summarize the study in one brief paragraph, stating the research design, the research question in terms of the hypotheses / variables measured, methodology, analysis, findings, and conclusion.

Introduction (12% of report marks)

You do not need to write a formal introduction or perform any background research. You only need to describe your three hypotheses based on the three relationships you chose to analyse.

For simplicity, this section can be organized with three headings:

Hypothesis 1:

Write one or two sentences stating your hypothesis for the first relationship you are analysing. Using the information provided earlier (pages 3-6), you need to indicate which variable is the predictor and which is being predicted. You also need to state the direction or sign (positive or negative) of the expected relationship. You may also comment on the expected strength, but that is not required.

Hypothesis 2:

Same as above but for the second relationship you are evaluating.

Hypothesis 3:

Same as above but for the third relationship you are evaluating.

Method (word limit: 400) (20% of report marks)

This entire section is to be written by you.

You need to include four sub-sections (each with a sub-heading):

Participants: describe the participants in the study (number; relevant demographic details; method of recruitment; reason for participation)

Design: identify the research design, what constructs were measured and how they were measured (operationalised to yield variables)

Materials: provide the specific details of the measurements taken, including any important details about any scales used

Procedure: describe the procedurehow the study was conducted

Ideally, the Method section should enable a person completely unfamiliar with the study to replicate exactly what you did.

Results (word limit: 300) (20% of report marks)

This section is to be written by you.

You need to:

describe how the data you are analysing was created from the information collected (if not already explained in the Method), including the range of possible scores.

explain how the data was explored, with appropriate references.

mention whether or not any data were excluded and give the reason why each item was excluded.

include a table of the means and standard deviations for the variables you used, labelled appropriately, and described in the text. Make sure your table is in APA format. The means and standard deviations should summarize the data AFTER any impossible scores are removed.

report each of the three correlations correctly and describe them in terms of the variables that are summarised.

report and describe the percentage of shared variance correctly.

Discussion (12% of report marks)

You do not need to write a full Discussion of your findings, only to summarise your results in relation to your initial hypotheses.

This section can be organized with the same three headings from the Introduction:

Hypothesis 1:

Indicate whether or not your hypothesis stated in the Introduction was supported - was the result in the expected direction? Use the shared variance to comment on the strength of relationship in some way (whether you made a hypothesis about the strength or not).

Hypothesis 2:

Same as above but for the second relationship you are evaluating.

Hypothesis 3:

Same as above but for the third relationship you are evaluating.

Appendices (26% of report marks)

This section is to be written by you.

You need to include:

Sample of the questionnaires. Although we completed the questionnaires online, a sample questionnaire document is in the Report folder on Blackboard.

Raw Data (copy of the data before any modifications)

Three Bivariate scatterplots for responses for the three relationships you choose to evaluate (identification of impossible observations, if any).

Three sets of full workings of Pearsons r

This means you should provide the specific values for the formula for Pearsons r :

r=ZxZyNYou should provide the values for numerator (ZXZY QUOTE ) and the denominator (N) of this formula. You dont need to provide all the z scores or the cross products.

Three sets of full workings of the percentage of shared variance between indicated variables.

Remember that anything you put in an appendix must be referred to in the body of the text.

Other points to remember:

The entire report must be double-spaced.

The report should have a title page.

Make sure you put the title at the beginning of the Introduction.

Put an appropriate running head on each page.

The word limits for the Abstract, Method and Results sections are maximum values. There is no minimum word count so long as you include all the relevant information in clearly written prose (NO DOT POINTS).

Use a font size of 12 to 14 points.

Recommended fonts: Times, Helvetica, Courier.

THE EMPTY TEMPLATE FOR YOUR REPORT IS A SEPARATE DOCUMENT.

Report Checklist:

Title page, including header

Abstract (8% of marks) 150 word limit

Report title

Introduction (12% of marks)

Three hypotheses from the choices given (can use subheadings here)

Method (20% of marks) 400 word limit

Participants

Design

Overall design

Variables measured and operationalisation

Materials

Questionnaire scale details

Procedure

Researcher instructions and participant task

Results (20% of marks) 300 word limit

Scoring of responses (if not in Method - Materials)

Exploration method

Data exclusions

Table of descriptive statistics for relevant hypothesis variables

Correlation analysis result

Percentage of shared variance (or coefficient of determination, but not both)

Discussion (12% of marks)

Support for three hypotheses from Introduction (can use the same subheadings as the Introduction)

Direction of results

Strength through shared variance

References (Not required)

Appendices (26% of marks)

Sample of Questionnaires (from the report materials folder)

Raw Data

Scatterplots of your three hypothesised relationships (raw data)

Correlation calculation from the equation provided for each hypothesis

Shared variance calculation for each hypothesis (can be combined with correlation as a single Appendix)

APA formatting (2% of marks)

Note that youll have to format the following template into APA style yourself. You can learn more about the APA style here:

https://apastyle.apa.org/style-grammar-guidelines7789331921932PSYC 1040

Psychology Research Methodology 1

2024 - Semester 1

Report Template

00PSYC 1040

Psychology Research Methodology 1

2024 - Semester 1

Report Template

Title Page [create this yourself this should be a page of its own]

Abstract [abstract goes on a page of its own]

(150 words maximum)

[start a new page for the introduction]

INSERT YOUR TITLE HERE this is the heading for the Introduction section.

This section can be organized with three headings:

Hypothesis 1:

You need to write one or two sentences stating your hypothesis for the first relationship you are evaluating. You need to indicate which is the predictor variable and which one is being predicted and you need to state the direction (sign, positive or negative) of the expected relationship.

Hypothesis 2:

Same as above but for the second relationship you are evaluating.

Hypothesis 3:

Same as above but for the third relationship you are evaluating.

Method

(400 words maximum)

Participants

Design

Materials

Procedure

Results

(300 words maximum)

Discussion

This section can be organized with three headings:

Hypothesis 1:

Indicate whether or not your hypothesis stated in the Introduction was supported. Was the result in the expected direction? Was the relationship as strong as you expected? Use shared variance to comment on the strength of relationship.

Hypothesis 2:

Same as above but for the second relationship you are evaluating.

Hypothesis 3:

Same as above but for the third relationship you are evaluating.

[Start a new page for Appendices, and each Appendix item should be on its own page]

Appendices

Provide the following in appropriately labelled appendices:

Sample of the questionnaires

Raw Data

Bivariate scatterplots

Full workings of correlation

Full workings of shared variance.