1. Main Themes Few vs. Many Variables Linear vs. Non-Linear Statistics vs. Machine Learning

2. Number of Variables Analyzed Week 1234567 6+ 5 4 3 2 1 Regression Correlation

3. Number of Variables / Observations A few variables vs. many variables A few observations vs. a ton of variables

4. Few Yes No Many Time Series Number of Variables PEW Mobile Phone Galton Children Height Census Text Sentiment Old Faithful Web Analytics Titanic Survivors Bank Loans Stock Market

5. Principle Components Analysis

6. People Variables Cluster Analysis

7. Linear Regression

10. Compare and Contrast

11. Tom Brady Not Tom Brady Machine Learning

12. Excel

13. R and Data Mining

14. Intermediate Book We will use the front part of chapters that are more conceptual, along with some of the case studies.