Class 1: Introduction to Data Science

• Variables, types of data (Nominal to Ratio), and the research cycle.

• Setting up your environment: Installing R, R Studio, and JASP. Familiarization to packages and their usages. 

Class 2: Descriptive Statistics & Visualizations

• Central Tendency (Mean, Median, Mode) and Dispersion (Standard Deviation, Variance).

• Types of visualizations and their uses.

• Basic Ideas for creating different visualizations in R and JASP.

• Tool Focus: Creating Histograms and Box-plots in JASP.

Class 3: Probability & Distribution

• The Normal Distribution, Z-scores, and the Central Limit Theorem.

• Tool Focus: Basic R syntax, loading datasets and using summary(). testing for distributions

Class 4: Hypothesis Testing Logic

• Null vs. Alternative hypotheses, p-values, and Type I/II errors.

• The "JASP Workflow": Drag-and-drop hypothesis testing.

• Testing of different hypothesis on R

Class 5: T-Tests (The Basics of Comparison)

• Independent and Paired samples t-tests.

• Tool Focus: Running t-tests in R using t.test() and interpreting JASP output.

Class 6: ANOVA (Analysis of Variance)

• Comparing three or more groups (One-way and Factorial ANOVA).

• Post-hoc testing and effect sizes.

• Visualizing ANOVA results using different plots

Class 7: Correlation & Association

• Pearson’s r, Spearman’s Rho, and Scatterplots.

• Tool Focus: Correlation matrices in JASP.

• Visualizing correlation matrices in R

Class 8: Linear Regression (Simple)

• Predicting outcomes and understanding the line of best fit ($y = mx + b$).

• Tool Focus: Simple linear models in R (lm()).

Class 9: Multiple Regression & Diagnostics

• Multi-predictor models and checking assumptions (Normality, Homoscedasticity).

Class 10: Categorical Data (Chi-Square)

• Tests of Independence and Goodness of Fit.

• Visualizing frequencies in R and JASP.

Class 11: Factor analysis

• Principle component analysis using R and JASP. 

Class 12: Data Storytelling & Final Showcase

• Best practices for reporting results (APA style).

• Automating reports in RStudio (RMarkdown/Quarto).