Udemy - Statistics for Your Dissertation - Choose, Run and Write Up

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Udemy - Statistics for Your Dissertation - Choose, Run and Write Up (Size: 1.2 GB)
  Bonus Resources.txt 102.4 B
  Get Bonus Downloads Here.url 204.8 B
  ~Get Your Files Here !
  1 - Module 1 The Big Picture & Workflow
  1. lecture 1.1 Welcome & The Big Picture (Description).html 1 KB
  1. lecture 1.1 Welcome & The Big Picture.mp4 8.5 MB
  10 - Module 10 Wrap‑Up & Next Steps
  2 - Module 2 Know Your Data First
  3 - Module 3 Use the Test Chooser Flowchart
  4 - Module 4 t-Tests Demystified
  10. Lecture 4.1 t‑Tests Demystified.mp4 20.9 MB
  11. Lecture 4.2 APA Write-Up Template for t-Tests.mp4 8.7 MB
  12. Lecture 4.3 Challenge Slide.mp4 2.6 MB
  5 - Module 5 ANOVA Without the Jargon
  13. Lecture 5.1 ANOVA Without the Jargon.mp4 25.2 MB
  14. Lecture 5.2 Post-Hoc Tests – What They Are & When to Use Them.mp4 11.7 MB
  15. Lecture 5.3 Challenge Slide.mp4 3.2 MB
  6 - Module 6 Chi-Square for Real-World Data
  16. Lecture 6.1 Chi‑Square for Real‑World Data.mp4 66.7 MB
  17. Lecture 6.2 Reading & Interpreting Chi-Square Output.mp4 55 MB
  18. Lecture 6.3 Challenge Slide.mp4 8.6 MB
  7 - Module 7 Correlation & Regression Made Easy
  19. Lecture 7.1 Correlation and Regression Made Easy.mp4 36 MB
  20. Lecture 7.2 Reading Correlation Output.mp4 116.7 MB
  21. Lecture 7.3 Challenge Slide.mp4 9.7 MB
  8 - Module 8 Doing It All in SPSS
  22. Lecture 8.1 Welcome to SPSS – Your New Best Friend.mp4 110.9 MB
  23. Lecture 8.2 Why Variable Setup Matters.mp4 103.4 MB
  24. Lecture 8.3 Why Descriptives Come First.mp4 35.6 MB
  25. Lecture 8.4 Running an Independent-Samples t-Test.mp4 97.1 MB
  26. Lecture 8.5 Running One-Way ANOVA.mp4 129.3 MB
  27. Lecture 8.6 Running Chi-Square Test.mp4 126.2 MB
  28. 3.Data Cleaning Checklist.pdf 297.2 KB
  28. Lecture 8.7 Running Pearson Correlation.mp4 98.8 MB
  9 - Module 9 Write Your Results Chapter Like a Pro
  29. 5.APA Phrase Bank.pdf 130.1 KB
  29. 7. Common Mistakes to Avoid.pdf 464.8 KB
  29. Chapter 4 Structure Template.pdf 440.6 KB
  29. Module 9 How to Structure Chapter 4 (Results).mp4 83.1 MB
  7. Lecture 3.1 Use the Test Chooser Flowchart.mp4 40.5 MB
  8. 1.Test Chooser Flowchart.pdf 255.8 KB
  8. Lecture 3.2 Relationship Between Categories → Chi-square.mp4 5.9 MB
  9. Lecture 3.3 Challenge Slide.mp4 4.6 MB
  4. 2. Assumption Checklists.pdf 254.9 KB
  4. Lecture 2.1 Know Your Data First.mp4 29.2 MB
  5. 4. Graph Selection Cheat Sheet.pdf 304.8 KB
  5. Lecture 2.2 Normality Explained Simply.mp4 9.3 MB
  6. Lecture 2.3 Challenge Slide.mp4 2.7 MB
  30. Module 10 Wrap-Up and Next steps.mp4 16 MB
  2. Lecture 1.2 The 4-step Dissertation stats workflow.mp4 2.7 MB
  3. Lecture 1.3 The Ultimate Test Chooser Flowchart.mp4 4.1 MB

Description


Statistics for Your Dissertation: Choose, Run & Write Up
https://WebToolTip.com
Published 4/2026

MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch

Language: English | Duration: 2h 26m | Size: 1.25 GB
Statistical test selection, results interpretation & Chapter 4 writing made simple
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
Requirements

Basic understanding of your research topic or dissertation question

Basic computer skills (e.g. opening files, using Excel or similar software)

Access to a dataset (your own research data or a practice dataset provided in the course)

Optional: Access to SPSS (helpful for the practical module, but not required to understand the concepts)

Willingness to apply the step-by-step methods to your own research project

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