Announcements! ( See All )
2/3 - Week 3 assignments have been posted! Quiz 1 on Thu 2/6 in your assigned section.

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

Holiday

Week 11

Fundamentals of Inference

Week 12

Continuous Distributions

Week 13

Bias and Variance

Week 14

Introduction to Regression

Week 15

Inference in Regression

WeekDateContentNotes & Assignments
1 Mon 01/20 No school
Tues 01/21 No school
Wed 01/22 Lecture 1: Course introduction and fundamentals (section 1.1, 1.2) Lecture 1 Notes
HW 1 (Due Mon 01/27 at 10 PM)
Thu 01/23 Discussion
Fri 01/24 Lecture 2: Exact calculations and bounds (section 1.3) Lecture 2 Notes
2 Mon 01/27 Lecture 3: Intersections of several events (section 2.1, 2.2) HW 2 (Due Mon 02/03 at 10 PM)
Lecture 3 Notes
Tues 01/28 Discussion
Wed 01/29 Lecture 4: Updating chances: Bayes' rule (section 2.3, 2.4) Lecture 4 Notes
Thu 01/30 Discussion
Fri 01/31 Lecture 5: A closer look at independence (section 2.4, 2.5) Lecture 5 Notes
3 Mon 02/03 Lecture 6: Random variables and their distributions: the binomial (section 3.1, 3.2, 3.3) HW 3 (Due Mon 02/10 at 10 PM)
Lecture 6 Notes
Tues 02/04 Discussion
Wed 02/05 Lecture 7: Simple random sampling (section 3.4, 3.5) Lecture 7 Notes
Thu 02/06 Quiz 1
Fri 02/07 Lecture 8: Exponential approximations (section 3.5, 4.1) Lecture 8 Notes
4 Mon 02/10 Lecture 9: Waiting time (section 4.2, 4.3) HW 4 (Due Tue 02/18 at 10 PM)
Lecture 9 Notes
Tues 02/11 Discussion
Wed 02/12 Lecture 10: Exponential approximation and Poisson Distribution (section 4.3, 4.4) Lecture 10 Notes
Thu 02/13 Discussion
Fri 02/14 Lecture 11: Poisson and Expectation (section 4.4, 5.1) Lecture 11 Notes
Lecture 11 Video Part1
Lecture 11 Video Part2
5 Mon 02/17 Holiday HW 5 (Due Mon 02/24 at 10 PM)
Tues 02/18 Discussion
Wed 02/19 Lecture 12: Expectation and Joint Distribution; (section 5.1, 5.2, 5.3) Lecture 12 Notes
Thu 02/20 Discussion
Fri 02/21 Lecture 13: The method of indicators and Additivity of Expectation (section 5.3)
6 Mon 02/24 Lecture 14: Indicators and Updating revisited: conditional distribution (section 5.3, 5.4)
Tues 02/25 Discussion
Wed 02/26 Lecture 15: Unbiased biased estimator(section 5.4, 5.5)
Thu 02/27 Quiz 2
Fri 02/28 Lecture 16: Expectation by conditioning (section 5.5)
7 Mon 03/02 Lecture 17: Expectation by conditioning continued (section 5.6)
Tues 03/03 Discussion
Wed 03/04 Midterm review
Thu 03/05 Discussion
Fri 03/06 Midterm
8 Mon 03/09 Lecture 18: Measuring variability (section 6.1, 6.2)
Tues 03/10 Discussion
Wed 03/11 Lecture 19: Typical or unusual? Tails of distributions (section 6.3, 6.4)
Thu 03/12 Discussion
Fri 03/13 Lecture 20: Variability of a random sample sum (section 7.1)
9 Mon 03/16 Lecture 21: The accuracy of a simple random sample (section 7.2)
Tues 03/17 Discussion
Wed 03/18 Lecture 22: The law of averages (section 7.3)
Thu 03/19 Discussion
Fri 03/20 Lecture 23: Central Limit Theorem (section 8.1, 8.2)
10 Mon 03/23 Holiday
Tues 03/24 Holiday
Wed 03/25 Holiday
Thu 03/26 Holiday
Fri 03/27 Holiday
11 Mon 03/30 Lecture 24: Normal approximations (section 8.3, 8.4)
Tues 03/31 Discussion
Wed 04/01 Lecture 25: Inference: testing hypotheses (section 9.1, 9.2)
Thu 04/02 Quiz 3
Fri 04/03 Lecture 26: Confidence intervals (section 9.3)
12 Mon 04/06 Lecture 27: Confidence intervals continue (section 9.4)
Tues 04/07 Discussion
Wed 04/08 Lecture 28: Probability density (section 10.1, 10.2)
Thu 04/09 Discussion
Fri 04/10 Lecture 29: The exponential distribution (section 10.3)
13 Mon 04/13 Lecture 30: Some properties of the normal distribution (section 10.4)
Tues 04/14 Discussion
Wed 04/15 Lecture 31: Prediction: bias-varaince (section 11.1)
Thu 04/16 Discussion
Fri 04/17 Lecture 32: The bias-variance tradeoff (section 11.2)
14 Mon 04/20 Lecture 33: Correlation (section 11.3, 11.4)
Tues 04/21 Discussion
Wed 04/22 Lecture 34: The regression estimates, effect and fallacy (section 11.4, 11.5)
Thu 04/23 Quiz 4
Fri 04/24 Lecture 35: The regression model for data (section 12.1)
15 Mon 04/27 Lecture 36: Inference for the true slope in the regression model (section 12.2, 12.3)
Tues 04/28 Discussion
Wed 04/29 Lecture 37: Conclusion
Thu 04/30 Discussion
Fri 05/01 Lecture 38: Review