Stat 88 · Probability and Mathematical Statistics for Data Science

Week 1

Getting Started

08/23-08/27

Week 2

Conditioning

08/30-09/03

Week 3

Random Variables

09/06-09/10

Week 4

Random Variables and Expectation

09/13-09/17

Week 5

The Power of Additivity

09/20-09/24

Week 6

Path to Prediction

09/27-10/01

Week 7

Midterm Week

10/04-10/08

Week 8

Variability

10/11-10/15

Week 9

Large Random Samples

10/18-10/22

Week 10

Fundamentals of Inference

10/25-10/29

Week 11

Continuous Distributions

11/01-11/05

Week 12

Bias and Variance

11/08-11/12

Week 13

Instroduction to Regression

11/15-11/19

Week 14

The Error in a Regression Estimate

11/22-11/26

Week 15

Inference in Regression

11/29-12/03

Week	Date	Content	Notes & Assignments
1	Mon 08/23	No school
	Tues 08/24	No school
	Wed 08/25	Lecture 1: Introduction and Syllabus, 1.1: Probabilities as Proportions	Lecture 1 Notes Lecture 1 Video HW 1 (Due 9/3 11:59PM)
	Thu 08/26	Discussion
	Fri 08/27	Lecture 2: 1.2: Exact Calculation and Bounds 1.3: Fundamental Rules	Lecture 2 Notes Lecture 2 Video
2	Mon 08/30	Lecture 3: 2.1: The Chance of an Intersection	Lecture 3 Notes Lecture 3 Video
	Tues 08/31	Discussion	Discussion Worksheet
	Wed 09/01	Lecture 4: 2.2: Symmetry in Simple Random Sampling 2.3: Bayes Rule	Lecture 4 Notes Lecture 4 Video HW 2 (Due 9/8 11:59PM)
	Thu 09/02	Discussion	Discussion Worksheet
	Fri 09/03	Lecture 5: 2.4: Uses and Interpretations 2.5: Independence	Lecture 5 Notes Lecture 5 Video
3	Mon 09/06	No School
	Tues 09/07	Discussion	Discussion Worksheet
	Wed 09/08	Lecture 6: 3.1: Success and Failure 3.2: Random Variables	Lecture 6 Notes Lecture 6 Video HW 3 (Due 9/15 11:59PM)
	Thu 09/09	Discussion
	Fri 09/10	Lecture 7: 3.3: Binomial Distribution 3.2: Hypergeometric Distribution	Lecture 7 Notes Lecture 7 Video
4	Mon 09/13	Lecture 8: 3.4 Examples	Lecture 8 Notes Lecture 8 Video
	Tues 09/14	Discussion	Discussion Worksheet
	Wed 09/15	Lecture 9: 4.1 Cumulative Distribution Functions	Lecture 9 Notes Lecture 9 Video HW 4 (Due 9/29 11:59PM)
	Thu 09/16	Discussion	Discussion Worksheet
	Fri 09/17	Lecture 10: 4.2: Waiting Times – Negative Binomial 4.3: Exponential Approximations	Lecture 10 Notes Lecture 10 Video
5	Mon 09/20	Lecture 11: 4.4: Poisson Distributions	Lecture 11 Notes Lecture 11 Video
	Tues 09/21	Discussion	Discussion Worksheet
	Wed 09/22	Lecture 12: 5.1: Definition 5.2: Functions of Random Variables	Lecture 12 Notes Lecture 12 Video HW 4 (Due 9/29 11:59PM)
	Thu 09/23	Discussion	Quiz 2 (On Gradescope) Discussion Worksheet
	Fri 09/24	Lecture 13: 5.2: Functions of Random Variables cont. 5.3: Methods of Indicators	Lecture 13 Notes Lecture 13 Video
6	Mon 09/27	Lecture 14: 2.1: 5.3: Methods of Indicators cont. 5.4: Unbiased Estimators	Lecture 14 Notes Lecture 14 Video
	Tues 09/28	Discussion	Discussion Worksheet
	Wed 09/29	Lecture 15: 5.5: Conditional Expectation 5.6: Expectation by Conditioning	Lecture 15 Notes Lecture 15 Video Homework 5 (Due 10/8)
	Thu 09/30	Discussion
	Fri 10/01	Midterm Review	Midterm Review Notes Midterm Review Video
7	Mon 10/04	Midterm
	Tues 10/05	Discussion
	Wed 10/06	Lecture 16: 6.1: Variance and Standard Deviation 6.2: Simplifying the Calculation	Lecture 16 Notes Lecture 16 Video Homework 6 (Due 10/13)
	Thu 10/07	Discussion	Discussion Worksheet
	Fri 10/08	Lecture 17: 6.3: Markov’s Inequality 6.4: Chebyshev's Inequality	Lecture 17 Notes Lecture 17 Video
8	Mon 10/11	Lecture 18: 7.1: Sum of Independent Random Variables	Lecture 18 Notes Lecture 18 Video
	Tues 10/12	Discussion	Discussion Worksheet
	Wed 10/13	Lecture 19: 7.2: Sampling without Replacement 7.3: Law of Averages	Lecture 19 Notes Lecture 19 Video Homework 7 (Due 10/20)
	Thu 10/14	Discussion	Discussion Worksheet
	Fri 10/15	Lecture 20: 8.1: Distribution of the Sample Sum (and the Sample Mean)	Lecture 20 Notes Lecture 20 Video
9	Mon 10/18	Lecture 21: 8.2: Standard Normal Curve
	Tues 10/19	Discussion
	Wed 10/20	Lecture 22: 8.3: Normal Approximation 8.4: How Large is Large
	Thu 10/21	Discussion
	Fri 10/22	Lecture 23: 9.1: Testing Hypotheses
10	Mon 10/25	Lecture 24: 9.2: A/B Testing: Fisher's Exact Test
	Tues 10/26	Discussion
	Wed 10/27	Lecture 25: 9.3: Confidence Intervals: Method
	Thu 10/28	Discussion	Quiz 3 (On Gradescope)
	Fri 10/29	Lecture 26: 9.4: Confidence Intervals: Interpretation
11	Mon 11/01	Lecture 27: 10.1: Density 10.2: Expectation and Variance
	Tues 11/02	Discussion
	Wed 11/03	Lecture 28: 8.1 - 9.4: Review of Statistical Inference
	Thu 11/04	Discussion
	Fri 11/05	Lecture 29: 10.4: Normal Distribution
12	Mon 11/08	Lecture 30: 11.1: Bias and Variance
	Tues 11/09	Discussion
	Wed 11/10	Lecture 31: 11.3: Least Squares Regression
	Thu 11/11	Discussion
	Fri 11/12	Lecture 32: 11.5: The Error in Regression
13	Mon 11/15	Lecture 33: 12.1: The Simple Linear Regression Model
	Tues 11/16	Discussion
	Wed 11/17	Lecture 34: 12.1: The Simple Linear Regression Model cont.
	Thu 11/18	Discussion	Quiz 4 (On Gradescope)
	Fri 11/19	Lecture 35: 12.2: The Distribution of the Estimated Slope
14	Mon 11/22	Lecture 36: 12.3: Towards Multiple Regression
	Tues 11/23	Discussion
	Wed 11/24	No School
	Thu 11/25	No School
	Fri 11/26	No School
15	Mon 11/29	Lecture 37: 12.3: Towards Multiple Regression cont.
	Tues 11/30	Discussion
	Wed 12/01	Lecture 38: Final Exam Review
	Thu 12/02	Discussion
	Fri 12/03	Lecture 39: Final Exam Review