1. Post-test Diagnostic - Linearity: Scatter plots and compare means, Heteroscedasticity: Glejser test, Autocorrelation/serial correlation - Durbin Watson
2. Hypothesis testing using Parametric tests - T tests (Independent t-test, Paired t-test), Z test, Anova
3. Hypothesis testing using Non Parametric tests - Chi-Square test (Cross-tabulation), Man Whitney U-test (2k independent Samples), Kruskal Wallis H-test (K independent Samples)
4. Transformation of Data - Recode into same variable, Recode into Different variables, Compute (logs, lag, averages, sum, products etc)

1. Categorical Regression analysis - Binary logistic regression, Multinomial logistic regression
2. Reliability and Validity test - Cronbach Alpha, KMO and Bartlet test
3. Factor Analysis - Communalities, Factor loadings, Scree Plots

Introduction to concept paper writing, structuring research ideas, identifying research gaps and formulating research objectives.

1. Chapter 1: Introduction
2. Chapter 2: Literature Review
3. Chapter 3: Methodology & Thesis Defense Preparation

1. Chapter 4: Data Analysis & Presentation — Understanding the purpose of Chapter 4, organising and structuring results/findings, quantitative data (tables, figures, charts), qualitative data (themes, categories, coding, narrative presentation)
2. Chapter 5: Discussion, Conclusion & Recommendations — The difference between results and discussion, interpreting and making meaning from findings, linking findings back to the literature review (Chapter 2)