This week’s topics
Advanced Inferential Statistics and Hypothesis Testing
- Multiple linear regression and multivariate analysis of variance
- Structural equation modeling and factor analysis fundamentals
- Testing hypotheses through p-values, confidence intervals, and effect sizes
- Interpreting statistical outputs for strategic decision-making
- MANOVA (Multivariate Analysis of Variance)
- Effect sizes and Bayes factors
- The Linear Model (Regression Part I)
What you will be able to do
- 3.4 Evaluate various statistical test for a given scenario and justify the chosen test.
- 3.5 Test the hypothesis with the most appropriate and draw meaningful conclusions.
- 6.1 Undertake qualitative and quantitative data analysis for a given dataset.
Activity
Start with this week’s 3 videos, then: Seminar, guided reading and a short written task: evaluate various statistical test for a given scenario and justify the chosen test.
Study materials
Videos
- MANOVA (Multivariate Analysis of Variance) · YouTube · Discover Statistics · 16 min · for registered students
- Effect sizes and Bayes factors · YouTube · Discover Statistics · 57 min · for registered students
- The Linear Model (Regression Part I) · YouTube · Discover Statistics · 51 min · for registered students
Further resources
- Principles of Data Science, ch. 4: Inferential Statistics and Regression Analysis · PDF · OpenStax, textbook chapter; pp. 155–222 · for registered students
- Learning Statistics with R (Navarro, v0.7.1), ch. 11: Hypothesis testing · PDF · Other, textbook chapter; pp. 439–469 · for registered students
- Research Methods in Psychology, ch. 13: Inferential Statistics · PDF · Saylor Academy, textbook chapter; pp. 342–377 · for registered students
Materials marked “for registered students” open in the student portal, which is set up as soon as you receive final acceptance.