| Date | Readings | Topic of Class |
| Jan. 10 |
No readings. |
Introduction. |
| 15 |
No class |
MLK Day |
| 17 |
WW 1. Designing Questions. |
Design of
surveys. |
| 22 |
WW 1. Using statistics to determine causal effects. |
Design of
experiments and observational studies. |
| 24 |
WW 2. |
Histograms, box plots, summary statistics. |
| 29 |
WW 11, 15.1. |
Scatter plots, correlations, line fitting, contingency tables. |
| 31 |
WW 3. |
Basics of probability. Conditional probability. |
| Feb. 5 |
WW 3. Supplement Section 2. |
Applications
of
probability. |
| 7 |
WW 4. Supplement Section 3. |
Random variables and probability distributions |
| 12 |
WW 4. Supplement Section 4. |
Expectations and variances. |
| 14 |
WW 5. Supplement Section 5. |
Joint distributions (discrete r.v. only). Covariance. |
| 19 |
WW 5. Supplement Section 5. | Review |
| 21 |
Midterm exam.
Link
to instructions for midterm 1. Project Proposal Due. Link to instructions for project |
|
| 26 |
WW 5. Supplement Section 6. |
Linear
combinations. |
| 28 |
Supplement Section 7. |
Linear
combinations. Iterated expectations. |
| Mar. 5 |
Supplement Section 7. WW 6. |
Sampling distributions.
Central limit theorem. |
| 7 |
WW 7. Supplement Section 8. |
Central limit
theorem. Bias. Efficiency. |
| 19 |
WW 8. |
Confidence
intervals (one sample). |
| 21 |
WW 8. |
More
confidence intervals (two samples). |
| 26 |
WW 9. |
Hypothesis
Tests (one sample). |
| 28 |
WW 9. |
More
hypothesis tests (two samples). |
| Apr. 2 |
WW 17. |
Chi-squared tests. |
| 4 |
WW 12. WW 15.2. |
Introduction to simple regression |
| 9 |
No readings. | Review |
| 11 |
Midterm exam. Link to instructions for midterm 2. | |
| 16 |
WW 12. WW 15.2. |
More on regression. |
| 18 |
WW 18. Supplement Section 9. |
Maximum likelihood estimation. |
| 19 |
Project presentations in labs. |
|
| 23 |
WW 19. |
Introduction to Bayesian statistics |
| 25 |
No reading. |
More Bayesian statistics. Wrap-up. |
| May 2 |
Final Exam, 7 PM - 10 PM. Link to instructions for final |