Announcements! ( See All )
1/18 - Welcome to STAT 88!!!

Week 1

Getting Started

Week 2

Conditioning

Week 3

Random Variables

Week 4

Random Variables and Expectation

Week 5

The Power of Additivity

Week 6

Path to Prediction

Week 7

Midterm Week

Week 8

Variability

Week 9

Large Random Samples

Week 10

Spring Recess

Week 11

Fundamentals of Inference

Week 12

Continuous Distributions

Week 13

Bias and Variance

Week 14

The Error in a Regression Estimate

Week 15

Inference in Regression

WeekDateContentNotes & Assignments
1 Mon 01/18 No school
Tues 01/19 No school
Wed 01/20 Lecture 1: Course introduction; fundamentals (section 1.1, 1.2)
Thu 01/21 Discussion
Fri 01/22 Lecture 2: Exact calculations, and bounds (section 1.3)
2 Mon 01/25 Lecture 3: Intersections of several events (section 2.1, 2.2)
Tues 01/26 Discussion
Wed 01/27 Lecture 4: Updating chances: Bayes' rule (section 2.3, 2.4)
Thu 01/28 Discussion
Fri 01/29 Lecture 5: A closer look at independence (section 2.4, 2.5)
3 Mon 02/01 Lecture 6: Random variables and their distributions: the binomial (section 3.1, 3.2, 3.3)
Tues 02/02 Discussion
Wed 02/03 Lecture 7: Simple random sampling (section 3.4, 3.5)
Thu 02/04 Discussion
Fri 02/05 Lecture 8: Exponential approximations (section 3.5, 4.1)
4 Mon 02/08 Lecture 9: Waiting Time (section 4.2, 4.3)
Tues 02/09 Discussion
Wed 02/10 Lecture 10: Exponential approximation and Poisson Distribution (section 4.3, 4.4)
Thu 02/11 Discussion
Fri 02/12 Lecture 11: Poisson and Expectation (section 4.4, 5.1)
5 Mon 02/15 No school
Tues 02/16 Discussion
Wed 02/17 Lecture 12: Expectation and Joint Distribution (section 5.1, 5.2, 5.3)
Thu 02/18 Discussion
Fri 02/19 Lecture 13: The power of Booleans: the method of indicators (section 5.3)
6 Mon 02/22 Lecture 14: Updating revisited: conditional distribution (section 5.3, 5.4)
Tues 02/23 Discussion
Wed 02/24 Lecture 15: Unbiased biased estimator (section 5.4, 5.5)
Thu 02/25 Discussion
Fri 02/26 Lecture 16: Expectation by conditioning (section 5.5)
7 Mon 03/01 Lecture 17: Examples: putting things together
Tues 03/02 Discussion
Wed 03/03 Midterm review
Thu 03/04 Discussion
Fri 03/05 Midterm
8 Mon 03/08 Lecture 20: Measuring variability (section 6.1, 6.2)
Tues 03/09 Discussion
Wed 03/10 Lecture 21: Typical or unusual? Tails of distributions (section 6.3, 6.4)
Thu 03/11 Discussion
Fri 03/12 Lecture 22: Variability of a random sample sum (section 7.1)
9 Mon 03/15 Lecture 23: The accuracy of a simple random sample (section 7.2)
Tues 03/16 Discussion
Wed 03/17 Lecture 24: The law of averages (section 7.3)
Thu 03/18 Discussion
Fri 03/19 Lecture 25: Central Limit Theorem (section 8.1, 8.2)
10 Mon 03/22 No school
Tues 03/23 No school
Wed 03/24 No school
Thu 03/25 No school
Fri 03/26 No school
11 Mon 03/29 Lecture 26: Normal approximations (section 8.3, 8.4)
Tues 03/30 Discussion
Wed 03/31 Lecture 27: Inference: testing hypotheses (section 9.1)
Thu 04/01 Discussion
Fri 04/02 Lecture 28: Inference: testing hypotheses (section 9.2) Continued
12 Mon 04/05 Lecture 29: Confidence intervals continue (section 9.3, 9.4)
Tues 04/06 Discussion
Wed 04/07 Lecture 30: Probability density (section 10.1, 10.2)
Thu 04/08 Discussion
Fri 04/09 Lecture 31: The exponential distribution (section 10.3)
13 Mon 04/12 Lecture 32: Some properties of the normal distribution (section 10.4)
Tues 04/13 Discussion
Wed 04/14 Lecture 33: Prediction: bias-variance (section 11.1)
Thu 04/15 Discussion
Fri 04/16 Lecture 34: The bias-variance tradeoff (section 11.2)
14 Mon 04/19 Lecture 35: Correlation (section 11.3, 11.4)
Tues 04/20 Discussion
Wed 04/21 Lecture 36: The regression estimates, effect and fallacy (section 11.4, 11.5)
Thu 04/22 Discussion
Fri 04/23 Lecture 37: The regression model for data (section 12.1)
15 Mon 04/26 Lecture 38: Inference for the true slope in the regression model (section 12.2, section 12.3)
Tues 04/27 Discussion
Wed 04/28 Lecture 39: Conclusion
Thu 04/29 Discussion
Fri 04/30 Lecture 40: Review