Statistical test selection, results interpretation & Chapter 4 writing made simple
Are you staring at your dissertation data thinking:
What you’ll learn
- Choose the correct statistical test (t-test, ANOVA, chi-square, correlation, regression) based on their research question and data type.
- Identify and correctly classify data types (nominal, ordinal, interval, ratio) and determine when to use parametric vs non-parametric tests.
- Interpret statistical results with confidence, including p-values, effect sizes, and key output tables.
- Run core statistical analyses in SPSS, including data setup, descriptives, t-tests, ANOVA, chi-square, correlation, and regression.
- Understand the difference between comparing groups and analysing relationships, and apply this to real research scenarios.
- Use a simple step-by-step workflow to move from raw data to a fully written Results (Chapter 4) section.
Course Content
- Module 1: The Big Picture & Workflow –> 3 lectures • 5min.
- Module 2: Know Your Data First –> 3 lectures • 9min.
- Module 3: Use the Test Chooser Flowchart –> 3 lectures • 9min.
- Module 4: t-Tests Demystified. –> 3 lectures • 10min.
- Module 5: ANOVA Without the Jargon –> 3 lectures • 10min.
- Module 6: Chi-Square for Real-World Data –> 3 lectures • 14min.
- Module 7: Correlation & Regression Made Easy –> 3 lectures • 19min.
- Module 8: Doing It All in SPSS –> 7 lectures • 57min.
- Module 9: Write Your Results Chapter Like a Pro –> 1 lecture • 8min.
- Module 10: Wrap‑Up & Next Steps –> 1 lecture • 5min.
Requirements
Are you staring at your dissertation data thinking:
- “Which statistical test do I use?”
- “What do these results actually mean?”
- “How do I turn this into a proper Chapter 4?”
You’re not alone — and this course is designed to fix exactly that.
What this course will help you do
By the end of this course, you will be able to:
- Choose the correct statistical test based on your research question and data
- Understand and interpret your results with confidence
- Avoid common mistakes that cost students marks
- Write clear, accurate, APA-style results for your dissertation
- Structure your Results (Chapter 4) in a way examiners expect
What makes this course different
This is not a theory-heavy statistics course.
You will not be overwhelmed with formulas or complex maths.
Instead, you’ll learn a clear, practical system to:
Choose → Run → Understand → Write
Everything is explained in plain English, using real examples you can apply directly to your own project.
What’s inside the course
- A simple step-by-step workflow from raw data to Chapter 4
- A test selection system you can use for any research project
- Clear explanations of key tests:
- t-tests
- ANOVA
- chi-square
- correlation
- regression
- How to interpret outputs (p-values, effect sizes, key statistics)
- How to write results using ready-to-use APA-style templates
- A full module on structuring your Results chapter
Downloadable tools included
You’ll also get practical resources you can use alongside your analysis:
- Test chooser flowchart
- Assumption checklists
- Data cleaning checklist
- Graph selection guide
- APA phrase bank
- Chapter 4 structure template
- Common mistakes checklist
Who this course is for
This course is ideal for:
- Undergraduate and master’s students working on a dissertation
- Students in psychology, health sciences, education, business, and social sciences
- Anyone who feels stuck choosing a test or writing their results
This course is NOT for
- Advanced statisticians
- Students looking for heavy mathematical theory
- Programming or data science professionals
Your outcome
By the end of this course, you will have a clear, repeatable system to take your data from analysis to a complete, high-quality Results chapter – without guessing.