| Week 1 Course Overview, introduction to Statistics |
| Course expectation and plan for success! |
| Recognize the different types of data and research questions |
| Week 2 Assumptions of statistical inference |
| Random variables, probability distribution, central limit theorem |
| Assumptions of statistical inference (larger sample size!) |
| Use R to graph and explain descriptive statistics of variables |
| Week 3 Hypothesis testing, significance level, t-statistics |
| Write hypotheses and interpret statistical results |
| Estimate the causal effects of experiments using differences of means |
| Week 4 Simple Linear Regression |
| Understand Best Linear Unbiased Estimator (BLUE) assumptions |
| Interpret and write regression results |
| Take home quiz 1 (due Mar 8 at 5pm): Study Week 1 to Week 3 |
| Week 5 Regression Diagnosis |
| Diagnose regression results |
| Recognize violation of assumptions |
| Week 6 Multiple Linear Regression, Omitted Variable Bias, Measures of fit |
| Interpret regression results |
| Diagnose model fitness and violation of assumptions |
| Week 7 Logarithm and Variable Transformation, Binary variables |
| Improve model fitness |
| Interpret regression results with transformed variable |
| **Week 8 Spring break – no lecture/lab |
| Take home quiz 2 (due Apr 26 at 5pm): Study Week 4 to Week 7 |
| Week 9 Interaction of independent variables |
| Improve model fitness |
| Interpret regression results with interaction terms |
| Week 10 Regression with Panel Data |
| (control for omitted variables that are constant across cases or time) |
| Familiarize panel data structure |
| Incorporate fixed effects to models |
| Week 11 Other Topics & Group Check-in |
| Week 12 Project Presentation |
| Week 13 Project Presentation |
| Final project Report due on May 19th Friday by 11:59 PM |