Advanced Analysis
25. Design of Experiments & Machine Learning
Introduction to Data Analytics and Python
Introduction to Data Analytics and Python
Pre-reading
Foundations
1. Introduction to Data Analytics
2. Experimental Design
Describing Data
3. Descriptive Statistics
4. Probability: Frequentist
5. Probability: Frequentist (cont) and Bayesian
6. Data Visualization
7. Statistics by Estimation
Inferential Statistics
8. Hypothesis Testing
9. Effect Sizes, p-Values, and Statistical Power
10. Comparing more than two samples
11. Non-normal data
12. Outliers and Transformations
13. Case Studies I
14. Bayesian Statistics: An Alternative to Hypothesis Testing
Modeling & Regression
19. Correlation and Simple Linear Regression
20. Multiple Linear Regression and Model Comparison
21. Nonlinear Regression
22. Analysis of Categorical and Discrete Outcomes
23. Case Studies II
Advanced Analysis
24. Multivariate Analysis and Dimensionality reduction
25. Design of Experiments & Machine Learning
Reference
Reference sheet: Choosing a Statistical Test
Practice Exam 1 (Sessions 1-14)
The Human in the Loop
Advanced Analysis
25. Design of Experiments & Machine Learning
25. Design of Experiments & Machine Learning
Updated
September 4, 2026
Note
This session will be released later in the semester.
24. Multivariate Analysis and Dimensionality reduction
Reference sheet: Choosing a Statistical Test