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. Case Studies I
13. Outliers, Data Blocking, and Transformations
14. Bayesian and beyond
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
Cheat Sheet: Choosing a Statistical Test
The Human in the Loop
Advanced Analysis
25. Design of Experiments & Machine Learning
25. Design of Experiments & Machine Learning
Note
This session will be released later in the semester.
24. Multivariate Analysis and Dimensionality reduction
Cheat Sheet: Choosing a Statistical Test