STA 240 Probability for Statistical Inference
Duke University Spring 2026
Below is a prospective outline for the course. Due dates are firm, but topics may change with advanced notice.
| WEEK | DATE | PREPARE | TOPIC | MATERIALS | DUE |
|---|---|---|---|---|---|
| 1 | Wed, Jan 7 | DS: 1.1 - 1.2 | Lec 1: Intro | ||
| Thu, Jan 8 | Lab 0: calculus review | Notes | |||
| 2 | Mon, Jan 12 | DS: 1.3 - 1.4 | Lec 2: Set theory | Notes | |
| Wed, Jan 14 | DS: 1.5 | Lec 3: Probability spaces | Notes | ||
| Thu, Jan 15 | Lab 1: hello R | Lab 1 @11:59 PM | |||
| Sun, Jan 18 | Pset 0 @11:59 PM | ||||
| 3 | Mon, Jan 19 | MLK Day - No class | |||
| Wed, Jan 21 | DS: 1.6-1.8 | Lec 4: Counting | Notes for Lec 4 and 5 | ||
| Thu, Jan 22 | Lab 2: counting | Lab 2 @11:59 PM | |||
| Sun, Jan 25 | Pset 1 @11:59 PM | ||||
| 4 | Mon, Jan 26 | DS: 1.6-1.8 | Lec 5: Counting | Zoom recording, Notes for Lec 4 and 5 | |
| Wed, Jan 28 | DS: 2 | Lec 6: Conditional probability | Notes, Play around! | ||
| Thu, Jan 29 | Lab 3: disease testing | Lab 3 @11:59 PM | |||
| Sun, Feb 1 | Problem 2 proof | Pset 2 @11:59 PM | |||
| 5 | Mon, Feb 2 | DS: 2 | Lec 7: Independence | Zoom recording, Notes | |
| Wed, Feb 4 | DS: 3.1, 3.3, 4.1 | Lec 8: Random variables intro | Notes | ||
| Thu, Feb 5 | Lab 4: ChatGPT | Lab 4 @11:59 PM | |||
| Sun, Feb 8 | Pset 3 @11:59 PM | ||||
| 6 | Mon, Feb 9 | DS: 5.1-5.4 | Lec 9: Discrete families | Notes | |
| Wed, Feb 11 | DS: 4.2 | Lec 10: Expected value | Notes | ||
| Thu, Feb 12 | Midterm 1 review | ||||
| Sun, Feb 15 | Pset 4 @11:59 PM | ||||
| 7 | Mon, Feb 16 | DS: 4.3 | Lec 11: Variance | Notes | |
| Wed, Feb 18 | Midterm 1 | ||||
| Thu, Feb 19 | Lab 5: random dating | Lab 5 @11:59 PM | |||
| 8 | Mon, Feb 23 | DS: 3.3 | Lec 12: Continuous random vars | Notes for Lec 12 and 13 | |
| Wed, Feb 25 | DS: 3.2 | Lec 13: Continuous random vars | |||
| Thu, Feb 26 | Lab 6: normal and gamma | Lab 6 @11:59 PM | |||
| 9 | Mon, Mar 2 | DS: 5.6-5.7 | Lec 14: Normal, gamma | Notes | |
| Wed, Mar 4 | DS: 4.4-4.5 | Lec 15: Moments and quantiles | Notes | ||
| Thu, Mar 5 | DS: 3.8 | Lab 7: transformations | Lab 7 @11:59 PM | ||
| 10 | Mon, Mar 9 | Spring Break - No classes | |||
| 11 | Mon, Mar 16 | DS: 4.4-4.5 | Lec 16: MGF | Notes | |
| Wed, Mar 18 | DS: 3.4-3.7 | Lec 17: Joint discrete r.v.’s | Notes | ||
| Thu, Mar 19 | DS: 12 | Lab 8: simulation | Lab 8 @11:59 PM | ||
| Sun, Mar 22 | Pset 5 @11:59 PM | ||||
| 12 | Mon, Mar 23 | DS: 3.4-3.7 | Lec 18: Joint continuous r.v.’s | Notes | |
| Wed, Mar 25 | DS: 6 | Lec 19: Sums and averages | Notes | ||
| Thu, Mar 26 | Midterm 2 review | ||||
| Sun, Mar 29 | Pset 6 @11:59 PM | ||||
| 13 | Mon, Mar 30 | DS: 6 | Lec 20: CLT | Notes | |
| Wed, Apr 1 | Midterm 2 | ||||
| Thu, Apr 2 | Lab 9: insurance | Lab 9 @11:59 PM | |||
| 14 | Mon, Apr 6 | Lec 21: What is statistics? | Notes | ||
| Wed, Apr 8 | Lec 22: What is statistics? | Notes: stats part 2, Notes: intro to MLE | |||
| Thu, Apr 9 | Lab 10: MLE | Lab 10 @11:59 PM | |||
| 15 | Mon, Apr 13 | Lec 23: Maximum likelihood | Notes | ||
| Wed, Apr 15 | Lec 24: MLE+intro to Bayes | Notes | |||
| Thu, Apr 16 | Lab 11: Bayes | Lab 11 @11:59 PM | |||
| 16 | Mon, Apr 20 | Lec 25: Bayesian inference | Notes | ||
| Wed, Apr 22 | Final exam review | ||||
| Sat, Apr 25 | Pset 7 @11:59 PM | ||||
| 17 | Mon, Apr 27 | Final exam (9am-12pm) |
