Spss Masterclass: A Comprehensive Course For Uni Students

Learn to run analyses on SPSS, interpret outputs with confidence, and report results in APA style like a pro.

What you'll learn

Enter Data Into SPSS

Run Analyses

Interpret Results

Reports Results in APA Style

Process Questionnaire Data

Reverse Coding

Assess Internal Reliability

Create Graphs

Check Assumptions

Independent T-tests

Paired T-Tests

Mann–Whitney U Tests

Wilcoxon Signed-Rank Tests

Chi-Squared Goodness of Fit Tests

Chi-Squared Tests of Independence

One-Way Independent ANOVA

One-Way Repeated-Measures ANOVA

Two-Way Independent ANOVA

Kruskal–Wallis Test

Friedman Test

Pearson Correlation

Spearman Correlation

Two–Way Mixed ANOVA

One-Way Independent ANCOVA

One-Way Independent MANOVA

Simple Linear Regression

Multiple Linear Regression

Binary Logistic Regression

Requirements

Students should have access to SPSS. The course videos were created in 2025 with version 30 of SPSS. There are only minor differences between versions, so the course is also suitable for students with other versions released around the same time. The student only needs to have knowledge of basic concepts, such as means, medians, and statistical significance. A free glossary defines all of the terms used in the course.

Description

Drawing on my BSc, MSc, and PhD degrees in psychology and neuroscience and over a decade of experience working with university students, especially those studying social sciences, I designed this course to cover the majority of analyses that students usually encounter in during their degrees.The Analyses Covered By the CourseThe course covers the following analyses: Independent t-testsMann–Whitney U tests Paired t-testsWilcoxon signed-rank testsChi-squared goodness of fit testsChi-squared tests of independenceOne-way independent (i.e., between-subjects) ANOVAsKruskal–Wallis testsOne-way repeated measures (i.e., within-subjects) ANOVAsFriedman testsTwo-way independent (i.e., between-subjects) ANOVAsPearson correlation analysesSpearman correlation analysesTwo-way mixed ANOVAsOne-way independent (i.e., between-subjects) ANCOVAsOne-way independent (i.e., between-subjects) MANOVAsSimple linear regressionMultiple linear regressionBinary logistic regressionAdditionally, the course covers how to process questionnaire data, focusing on entering data, identifying and labelling invalid responses, reverse coding, internal reliability, and creating mean (i.e., average) and sum (i.e., total) scores.  What You’ll LearnFor each of the analyses, you’ll receive clear, step-by-step guidance on when to use them, how to enter the data, how to check assumptions, how to run the test, how to create a graph, how to interpret the results, and how to report the results in APA style. With this knowledge, you’ll be a step ahead of your university peers!ResourcesEach section of the course focuses on a different analysis and comes with a range of valuable resources, including the data files used in the videos, information sheets with key details about the analyses (e.g., when to use them, example hypotheses, assumptions), and example APA results sections. You’ll also receive a glossary explaining all the terms used in the videos.AssignmentsEach section comes with an additional data set (not used in the videos) that you can use to practice running the analysis and reporting the results. If you choose to complete the assignments, you can download example results sections based on these data sets to assess whether you ran the test correctly and how accurately you reported the results.

Overview

Section 1: Processing Questionnaire Data

Lecture 1 Introduction

Lecture 2 Processing Questionnaire Data Introduction

Lecture 3 Entering Questionnaire Data

Lecture 4 Invalid Responses, Reverse Code, Internal Reliability, Mean & Sum Scores

Section 2: Independent T-Tests

Lecture 5 An Introduction to Independent T-Tests and Entering Data

Lecture 6 Check Assumptions, Run T-test, Create Graph

Lecture 7 Interpret and Report T-Test Results

Section 3: Mann–Whitney U Tests

Lecture 8 An Introduction to Mann–Whitney U Tests and Entering Data

Lecture 9 Run Mann–Whitney U Test and Create a Graph

Lecture 10 Interpret and Report Mann–Whitney U Test Results

Section 4: Paired T-Tests

Lecture 11 An Introduction to Paired T-Tests and Entering Data

Lecture 12 Check Assumptions, Run T-test, Create Graph

Lecture 13 Interpret and Report Paired T-Test Results

Section 5: Wilcoxon Signed-Rank Tests

Lecture 14 An Introduction to Wilcoxon Signed-Rank Tests and Entering Data

Lecture 15 Run Wilcoxon Signed-Rank Test

Lecture 16 Interpret and Report Wilcoxon Signed-Rank Test Results

Section 6: Chi-Squared Goodness of Fit Tests

Lecture 17 An Introduction to Chi-Squared Goodness of Fit Tests and Entering Data

Lecture 18 Run Chi-Squared Goodness of Fit Test and Make a Graph

Lecture 19 Check Assumptions and Interpret and Report Chi-Squared Test Results

Section 7: Chi-Squared Tests of Independence

Lecture 20 An Introduction to Chi-Squared Tests of Independence and Entering Data

Lecture 21 Run Chi-Squared Test of Independence and Make a Graph

Lecture 22 Check Assumptions and Interpret and Report Chi-Squared Test Results

Section 8: One-Way Independent ANOVA

Lecture 23 An Introduction to One-Way Independent ANOVAs and Entering Data

Lecture 24 Check Normality Assumption, Run One-Way Independent ANOVA, Create Graph

Lecture 25 Check HoV Assumption, Interpret and Report One-Way Independent ANOVA Results

Section 9: Kruskal–Wallis Test

Lecture 26 An Introduction to Kruskal–Wallis Tests and Entering Data

Lecture 27 Run Kruskal–Wallis Test and Create a Graph

Lecture 28 Interpret and Report Kruskal–Wallis Test Results

Section 10: One–Way Repeated Measures ANOVA

Lecture 29 An Introduction to One-Way Repeated Measures ANOVAs and Entering Data

Lecture 30 Check Normality Assumption, Run One-Way Repeated Measures ANOVA and Make a Graph

Lecture 31 Check Sphericity Assumption, Interpret and Report ANOVA Results

Section 11: Friedman Test

Lecture 32 An Introduction to Friedman Tests and Entering Data

Lecture 33 Run Friedman Test and Make a Graph

Lecture 34 Interpret and Report Friedman Test Results

Section 12: Two-Way Independent ANOVA

Lecture 35 An Introduction to Two-Way Independent ANOVAs and Entering Data

Lecture 36 Check Normality Assumption, Run ANOVA, and Make a Graph

Lecture 37 Check HoV Assumption, Interpret and Report Two-Way Independent ANOVA Results

Section 13: Two-Way Mixed ANOVA

Lecture 38 An Introduction to Two-Way Mixed ANOVAs and Entering the Data

Lecture 39 Check Assumptions, Create Graph, Run Analysis, Interpret Results

Lecture 40 Reporting the Results of the Two-Way Mixed ANOVA

Section 14: One-Way Independent ANCOVA

Lecture 41 An Introduction to One-Way Independent ANCOVAs and Entering the Data

Lecture 42 Check Assumptions, Create Graph, Run Analysis, Interpret Results

Lecture 43 Reporting the Results of the One-Way Independent ANCOVA

Section 15: One-Way Independent MANOVA

Lecture 44 An Introduction to One-Way Independent MANOVAs and Entering the Data

Lecture 45 Check Normality, Outliers, and Linearity Between the Dependent Variables

Lecture 46 Check Other Assumptions, Run Analysis, Create Graph, Interpret Results

Lecture 47 Reporting the Results of the One-Way Independent MANOVA

Section 16: Pearson Correlation

Lecture 48 An Introduction to Pearson Correlation and Entering Data

Lecture 49 Check Assumptions, Create Figure, and Run Pearson Correlation Analysis

Lecture 50 Interpret and Report Pearson Correlation Analysis Results

Section 17: Spearman Correlation

Lecture 51 Introduction to Spearman Correlation and Entering Data

Lecture 52 Run Spearman Correlation Analysis and Create a Figure

Lecture 53 Interpret and Report Spearman Correlation Analysis Results

Section 18: Simple Linear Regression

Lecture 54 An Introduction to Simple Linear Regression and Entering the Data

Lecture 55 Check Assumptions, Create Graph, Run Analysis, Interpret Results

Lecture 56 Reporting the Results of the Simple Linear Regression

Section 19: Multiple Linear Regression

Lecture 57 An Introduction to Multiple Linear Regression and Entering the Data

Lecture 58 Check Assumptions, Create Graph, Run Analysis, Interpret Results

Lecture 59 Reporting the Results of the Multiple Linear Regression

Section 20: Binary Logistic Regression

Lecture 60 An Introduction to Binary Logistic Regression and Entering the Data

Lecture 61 Check Assumptions, Run Analysis, Interpret Results

Lecture 62 Reporting the Results of the Binary Logistic Regression

University students, especially those studying social science subjects (e.g., psychology), who need to use SPSS for their research methods classes.