PSGY1001
Preface
How to use this book
Weekly overview
Lab 1 (w/c 3 Oct)
Lab 2 (w/c 10 Oct)
Lab 3 (w/c 17 Oct)
w/c 24 Oct
Lab 4 (w/c 31 Oct)
Lab 5 (w/c 7 Nov)
Lab 6 (w/c 14 Nov)
Lab 7 (w/c 21 Nov)
Lab 8 (w/c 28 Nov)
Lab 9 (w/c 5 Dec)
Lab 10 (w/c 12 Dec)
Lab 11 (w/c 30 Jan)
Lab 12 (w/c 6 Feb)
Lab 13 (w/c 13 Feb)
w/c 20 Feb
Lab 14 (w/c 27 Feb)
Lab 15 (w/c 6 Mar)
Lab 16 (w/c 13 Mar)
Lab 17 (w/c 20 Mar)
Lab 18 (w/c 27 Mar)
Lab 19 (w/c 1 May)
Lab 20 (w/c 8 May)
Lab 1
1
People and support
1.1
Lecturers and demonstrators
1.2
Help desk
1.3
Moodle page and forum
1.4
Email and personal Teams chat
1.5
IT support
1.6
End-of-chapter quiz
2
Lab classes and module content
2.1
The lab classes
2.2
Module content in brief
2.3
Workload
2.4
School vs uni
3
Assessment overview
3.1
Summative assessments
3.2
Research participation scheme
3.3
Overall mark calculation
3.4
Academic misconduct
3.5
Extenuating circumstances
3.5.1
Summative assessments
3.5.2
Formative assessments
3.6
Disability support
3.7
End-of-chapter quiz
4
Getting started
4.1
Core reading
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
End-of-chapter quiz
5
Moodle forum post
6
Lab 1 Padlet
Lab 2
7
Scientific reasoning
7.1
Research producers and research consumers
7.2
Empiricism
7.3
Conceptual and operational definitions
7.4
Ask a research question
8
Design a study
8.1
Introduction
8.2
Your task
8.3
Meet your team
8.4
Examples of German humour
8.5
Humour study design results
9
Quiz 1
10
Lab 2 Padlet
Lab 3
11
Ethics
12
Identifying good measurement
13
Lab 3 Padlet
Lab 4
14
Experiments
14.1
Simple vs choice RT
15
A closer look at attrition
16
Interference tasks
17
Avital-Cohen activity
18
Quiz 2
19
Lab 4 Padlet
Lab 5
20
PsychoPy basics
20.1
Install PsychoPy
20.2
Download and unzip a flanker experiment
20.3
Open an experiment
20.4
Run an experiment
20.5
Quit an experiment
20.6
Save an experiment
21
The Builder and its parts
21.1
Components
21.2
Routines
21.3
Naming components and routines
21.4
The flow
21.5
The toolbar
21.5.1
Monitor and experiment settings
21.5.2
Compile and run experiments
22
Components and their properties
22.1
Text component
22.2
Image component
22.3
Keyboard component
22.4
Building a Stroop task from scratch
23
Lab 5 exercises
23.1
Exercise 1
23.2
Exercise 2
23.3
Exercise 3
23.4
Challenge exercises
23.4.1
Exercises 1 and 2
23.4.2
Exercise 3
24
Lab 5 Padlet
Lab 6
25
Beyond the single trial
25.1
Input file basics
25.2
PsychoPy loops
25.2.1
Loop properties
25.2.2
Adding and removing a loop
26
Using information from input files
26.1
Defining a stimulus
26.2
Determining a correct response
26.3
Adding additional information to the output file
27
Lab 6 exercises
27.1
Main exercise
27.2
Challenge exercise
28
Formative PsychoPy assignment
29
Lab 6 Padlet
Lab 7
30
Giving feedback
31
Miscellanea
31.1
PsychoPy processes components from top to bottom
31.2
Skipping routines
31.3
Copying and pasting routines and components
31.4
PsychoPy demos
31.5
Spatial units in Psychopy
32
Lab 7 exercise
33
Lab 7 Padlet
Lab 8
34
Lab 8 exercise
35
PsychoPy output files
35.1
Location of output files
35.2
The output file name
35.3
Output file basics
35.4
Output file rows
35.5
Output file columns
35.6
Challenge exercise
36
Summative PsychoPy assignment
36.1
Overall results
37
Lab 8 Padlet
Lab 9
38
Excel basics
38.1
Columns, rows, and cells
38.2
Cut, copy, and paste
38.3
Selecting content
38.4
Deleting cells, rows or columns
38.5
Automatically adjusting column width
38.6
Sorting data
38.7
Data formats
38.8
Relative vs. absolute cell references
39
Excel formulas and functions
39.1
Formulas
39.1.1
Basic arithmetic operators
39.2
Functions
39.2.1
IF
39.2.2
SUM
39.2.3
AVERAGE
39.2.4
Other functions
39.3
Copying formulas
40
Lab 9 Padlet
Lab 10
41
Introduction to data preprocessing
41.1
What we get from PsychoPy and what we need for SPSS
41.2
How to get from PsychoPy output to SPSS input
42
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)
42.1
Calculating medians
42.2
Comparison of means with and without outlier removal and medians
42.3
Evaluation
42.4
Preprocessing Shiny app
43
Data preprocessing with R
44
January exam
45
Lab 10 Padlet
Lab 11
46
SPSS basics
46.1
Installing SPSS
46.2
Background
46.3
Getting help with SPSS
46.4
Getting data into SPSS
46.4.1
Importing data
46.4.2
Entering data
46.4.3
Opening existing data
46.5
Types of files
46.6
Types of windows
46.7
Computing new variables
46.8
Free SPSS alternatives
47
SPSS preprocessing
47.1
Checking the level of measurement
47.2
Defining missing values
47.3
Adding variable and value labels
48
Lab 11 exercises
48.1
Exercise 1
48.2
Exercise 2
49
Lab 11 Padlet
Lab 12
50
Descriptives for categorical data
50.1
Selecting and sorting variables
50.2
Calculating descriptive statistics
50.3
Recoding variables
51
Descriptives for continuous data
51.1
Calculating descriptive statistics
51.2
Boxplots
51.3
Removing participants from SPSS data files
52
Lab 12 exercises
52.1
Exercise 1
52.2
Exercise 2
53
Quiz 3
53.1
Excel quiz walk-through
54
Lab 12 Padlet
Lab 13
55
Intro to inferential statistics
55.1
Inferential statistics quiz
55.2
Standard normal distribution basics
55.3
The basic logic of null hypothesis significance testing (NHST)
55.4
Distributions of participant means vs. sampling distributions
56
The one-sample
t
-test
56.1
Running the one-sample
t
-test
56.2
The one-sample
t
-test SPSS output
56.3
Interpreting the output
56.4
A step-by-step
t
-test in Excel
56.5
The trouble with
t
and
p
-values
56.6
Computing the effect size
56.7
Reporting the results of a one-sample
t
-test
57
Lab 13 exercise
58
Lab 13 Padlet
Lab 14
59
The Pearson correlation test
59.1
Running the Pearson correlation test
59.2
The Pearson correlation test output
59.3
What does the output mean?
59.4
A step-by-step correlation test in Excel
59.5
The effect size for a Pearson correlation test
59.6
Reporting the results of a Pearson correlation analysis
60
Lab 14 exercise
61
Excel/SPSS data analysis quiz
62
Lab 14 Padlet
Lab 15
63
Lab report basics
64
Lab 15 Padlet
Lab 16
65
Lab report template and marking rubric
65.1
The lab report template
65.2
The marking rubric
66
Lab 16 exercise
67
Summative lab report experiment
68
The formative lab report
69
Lab 16 Padlet
Lab 17
70
Lab 17 exercise
71
Lab 17 Padlet
Lab 18
72
Creating charts
72.1
Excel bar chart
72.2
SPSS bar chart
72.3
jamovi and ESCI
73
Lab 18 exercise
74
The summative lab report
75
Lab 18 Padlet
Lab 19
76
Formative lab report feedback
77
Lab 19 Padlet
Lab 20
78
Formative lab report examples
79
Lab 20 exercise
80
References
Appendices
A
Semester overview
A.1
Autumn semester
A.2
Spring semester
B
Glossary
C
Moodle forum settings
D
Psychology in the news
D.1
2021/22
E
MS Teams
E.1
Create a group on Teams and add members
E.2
Scheduling a meeting for a team
E.3
Contacting Team members
E.4
Viewing names of Team members
E.5
Notification settings
F
Sharing an online Word document
G
Searching literature - a very brief intro
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
Chapter 76
Formative lab report feedback
You can
download the formative lab report feedback slides here
.