✓R Programming & Data Wrangling
✓R programming for data analysis
✓Writing clean reproducible R code
✓Tidyverse data manipulation skills
✓Data wrangling with dplyr and tidyr
✓Visualizing data with ggplot2
✓Handling messy, real-world datasets
✓Creating clear, professional plots
✓Organizing projects for reproducibility
✓GitHub code-along scripts included
✓Core Statistical Concepts
✓Understanding sampling variability
✓Exploring statistical distributions
✓Central limit theorem in practice
✓Standard error and confidence intervals
✓Logic of hypothesis testing
✓Null vs alternative hypotheses
✓P-values and significance testing
✓Comparing statistical tests effectively
✓Building analytic intuition hands-on
✓Inferential Statistics & Modeling
✓Conducting t-tests in R
✓ANOVA and group comparisons
✓Chi-square test for categorical data
✓Linear regression modeling in R
✓Understanding assumptions of tests
✓Interpreting effect sizes in R
✓Practical Data Analysis
✓Realistic messy data scenarios
✓Iterative analysis and refinement
✓Making decisions with uncertainty
✓Interpreting results like a researcher
✓Guided exercises for practice
✓Step-by-step code demonstrations
✓Building confidence as a data analyst
✓Applying statistics to real projects