PSGY1001
Introduction
How to use this book
1
Weekly overview
Lab 1 (w/c 4 Oct)
Lab 2 (w/c 11 Oct)
Lab 3 (w/c 18 Oct)
Lab 4 (w/c 25 Oct)
Lab 5 (w/c 1 Nov)
w/c 8 Nov
Lab 6 (w/c 15 Nov)
Lab 7 (w/c 22 Nov)
Lab 8 (w/c 29 Nov)
Lab 9 (w/c 6 Dec)
Lab 10 (w/c 13 Dec)
Lab 11 (w/c 31 Jan)
Lab 12 (w/c 7 Feb)
Lab 13 (w/c 14 Feb)
w/c 21 Feb
Lab 14 (w/c 28 Feb)
Lab 15 (w/c 7 Mar)
Lab 16 (w/c 14 Mar)
Lab 17 (w/c 21 Mar)
Lab 18 (w/c 28 Mar)
Lab 19 (w/c 4 Apr)
w/c 11 Apr
Lab 20 (w/c 2 May)
2
PSGY1001: Key facts
2.1
Lecturers and demonstrators
2.2
Module content
2.3
Workload
2.4
In-person and online support
2.4.1
The lab meetings
2.4.2
The help desk
2.4.3
The Moodle page and forum
2.4.4
E-mail and personal Teams chat
2.4.5
IT support
2.5
Assessment
2.5.1
The Rogo exam
2.6
Research participation scheme (RPS)
2.7
Disability support and accessibility
2.8
Extenuating circumstances
2.8.1
Summative assignments
2.8.2
Formative assignments
2.9
School vs uni
3
TV shows data exploration
4
Getting started
4.1
Beth Morling’s research methods book
4.2
Computer setup
4.2.1
General computer setup
4.2.2
Software to install
4.2.3
OneDrive
4.2.4
Note-taking
4.3
Moodle forums
4.4
Your first lab Moodle forum post
4.5
Your first study
5
Scientific reasoning
5.1
Research producers and research consumers
5.2
Empiricism
5.3
Conceptual and operational definitions
5.4
Quiz 1
5.4.1
Quiz FAQs
5.5
Lab 2 Padlet
6
Design a study
6.1
Introduction
6.2
Your task
6.3
Meet your team
6.4
Examples of German humour
6.5
Humour study design outcomes
7
Ethics and good measurement
7.1
Ethical guidelines
7.2
Identifying good measurement
7.3
Your first study, Part II
7.4
Lab 3 Padlet
8
Experiments
8.1
Quiz 2
8.2
Lab 4 Padlet
9
Interference tasks
9.1
Introduction
9.2
Read the research activity
PsychoPy
10
PsychoPy basics
10.1
Installing PsychoPy
10.1.1
Alternatives to installing PsychoPy on your own computer
10.2
Opening, running and saving experiments
10.2.1
Opening an experiment
10.2.2
Running an experiment
10.2.3
Saving an experiment
11
The Builder and its parts
11.1
Components
11.2
Routines
11.3
Naming components and routines
11.4
The flow
11.5
The toolbar
11.5.1
Monitor and experiment settings
11.5.2
Compiling, running and quitting an experiment
12
Components and their properties
12.1
Text component
12.2
Image component
12.3
Keyboard component
12.4
Building a Stroop task from scratch
12.5
Lab 5 Padlet
13
Lab 5 exercises
13.1
Exercise 1
13.2
Exercise 2
13.3
Exercise 3
13.4
Challenge exercises
13.4.1
Exercises 1 and 2
13.4.2
Exercise 3
14
Beyond the single trial
14.1
Input file basics
14.2
PsychoPy loops
14.2.1
Loop properties
14.2.2
Adding and removing a loop
15
Using information from input files
15.1
Defining a stimulus
15.2
Determining a correct response
15.3
Adding additional information to the output file
15.4
Lab 6 Padlet
16
Lab 6 exercise and formative PsychoPy assignment
16.1
Lab 6 exercise
16.2
Formative PsychoPy assignment
16.2.1
Effect of submitting the formative PsychoPy assignment
16.3
Lab 6 challenge exercise
16.4
Quick survey
17
Giving feedback
18
Miscellenea
18.1
Colour picker
18.2
PsychoPy processes components from top to bottom
18.3
Skipping routines
18.4
Copying and pasting routines and components
18.5
PsychoPy demos
18.6
Lab 7 Padlet
19
Lab 7 exercise
20
PsychoPy output files
20.1
Location of output files
20.2
The output file name
20.3
File content
20.3.1
What are the rows?
20.3.2
What information is in the columns?
20.4
Lab 8 Padlet
21
Summative PsychoPy assignment
Data preprocessing
22
Excel basics
22.1
Columns, rows, and cells
22.2
Cut, copy, and paste
22.3
Selecting cells, columns, rows, and spreadsheets
22.4
Deleting cells, rows or columns
22.5
Automatically adjusting column width
22.6
Sorting data
22.7
Data formats
22.8
Relative vs. absolute cell references
23
Excel formulas and functions
23.1
Formulas
23.1.1
Basic arithmetic operators
23.2
Functions
23.2.1
IF
23.2.2
SUM
23.2.3
AVERAGE
23.2.4
Other functions
23.3
Copying formulas
23.4
Lab 9 Padlet
24
The value of reaction times and error rates in psychology
25
Introduction to data preprocessing
25.1
What we get from PsychoPy and what we need for SPSS
25.2
How to get from PsychoPy output to SPSS input
26
Data preprocessing with Excel
Step 1: Converting reaction times to milliseconds
Step 2: Calculating the overall accuracy
Step 3: Removing trials with extreme RTs
Step 4: Calculating condition-specific accuracies
Step 5: Calculating condition-specific mean RTs (before outlier removal)
Step 6: Calculating SDs and thresholds for outlier removal
Step 7: Calculating condition-specific mean RTs (after outlier removal)
26.1
Calculating medians
26.2
Comparison of means with and without outlier removal and medians
26.3
Evaluation
26.4
Lab 10 Padlet
27
Data preprocessing with R
SPSS
28
SPSS basics
28.1
Installing SPSS
28.2
Introduction to SPSS
28.3
Getting help with SPSS
28.4
Types of files
28.5
Types of windows
28.6
Getting data into SPSS
28.6.1
Importing data
28.6.2
Entering data
28.6.3
Opening existing data
28.7
Computing new variables
28.8
Free SPSS alternatives
28.9
SPSS basics exercise
29
Intro to descriptive statistics
29.1
Checking the level of measurement
29.2
Lab 12 Exercise 1
29.3
Defining missing values
30
Descriptives for categorical data
30.1
Lab 12 Exercise 2
31
Descriptives for continuous data
32
Descriptive statistics - next steps
32.1
Removing participants with missing data
32.2
Adding variable and value labels
32.3
Descriptive statistics after screening and cleaning
32.4
Lab 12 Exercise 3
33
The Excel quiz
33.1
Excel quiz walkthrough
34
Intro to inferential statistics
34.1
Inferential statistics quiz
34.2
Standard normal distribution basics
34.3
The basic logic of null hypothesis significance testing (NHST)
34.4
Distributions of participant means vs. sampling distributions
35
Rejecting outliers based on SDs
36
The one-sample
t
-test
36.1
Running the one-sample
t
-test
36.2
The one-sample
t
-test SPSS output
36.3
Interpreting the output
36.4
Lab 13 Exercise
36.5
The trouble with
t
and
p
-values
36.6
Computing the effect size
36.7
Reporting the results of a one-sample
t
-test
37
The Pearson correlation test
37.1
Running the Pearson correlation test
37.2
The Pearson correlation test output
37.3
What does the output mean?
37.4
Lab 14 exercise
37.5
The effect size for a Pearson correlation test
37.6
Reporting the results of a Pearson correlation analysis
38
RPS reminder
39
Excel/SPSS data analysis quiz
Lab reports
40
Lab report basics
41
Lab report template and marking rubric
41.1
The lab report template
41.2
The marking rubric
42
The formative lab report
43
Creating charts
43.1
Excel bar chart
43.2
ESCI point plot
43.3
SPSS bar chart
44
Xerte activities
45
Endnote
45.1
Installing EndNote
45.2
Accessing Web of Science and importing a reference
45.3
Exporting from Google Scholar to EndNote
45.4
Adding APA7 style to EndNote output style
45.5
Manual interventions
45.6
More EndNote resources
45.7
Alternatives to EndNote
46
The summative lab report
47
Formative lab report feedback
48
References
Appendices
A
Semester overview
A.1
Autumn semester
A.2
Spring semester
B
Glossary
C
Moodle forum digest settings
D
MS Teams
D.1
Create a group on Teams and add members
D.2
Scheduling a meeting for a team
D.3
Contacting Team members
D.4
Viewing names of Team members
D.5
Notification settings
E
Searching literature - a very brief intro
F
Sharing an online Word document
G
Psychology in the news
H
PsychoPy issues
H.1
Checking your experiment
H.2
PsychoPy error messages
H.3
Getting help
I
Python basics
Made with bookdown
The Hitchhiker’s Guide to PSGY1001
B
Glossary
The glossary below introduces some key terms and abbreviations.