Prof: | Sayan Mukherjee |
sayan@stat.duke.edu | OH: Wednesday 2:15-3:15 | 112 Old Chem | |

TAs: | |||||

Yimeng Jia | OH: | Wed. 12-1, Fri 9-10, 221A Old Chem | |||

Liyu Gong | OH: | Mon 11:30-12:30, Fri 11:30-12:30, 221A Old CHem | |||

Wenli Shi | OH: | Tue 11:30-12:30, Th 11:30-12:30 221A Old Chem | |||

Class: | T/Th 1:25-2:40pm | Old Chem 116 |

The course text is Jim Pitman, Probability. You will also have access to Elementary Probability for Applications by Rick Durrett on Sakai.

In the syllabus below I have posted for each lecture what section in Pitman or Durrett the material is covered in.

I have also posted in the syllabus below links to video lectures by Jonathan Mattingly and Joe Blitzstein that cover the lecture material as well.

For each lecture (typically one lecture will cover two classes). I have posted where in both books the material is covered, links to videos covering the material, a short note on the key topics/ideas, in these lectures, and the homework.

The homework, quiz, and exam scores will be reported through Sakai. Also before every class you will be expected to take a short quiz. This is to make sure you have looked at the material before class.

No make-up exams will be given and there will be no make-ups for homeworks or quizes. You cannot pass the class if you do not take the final.

Homework is graded out of 100. Late work will receive no credit. Lowest homework score will be dropped. Even if you have an excused absence you must turn in your homework.

There is a Piazza course discussion page. Please direct questions about homeworks and other matters to that page. Otherwise, you can email the instructors (TAs and professor) at sta230-ta@duke.edu. Note that we are more likely to respond to the Piazza questions than to the email, and your classmates may respond too, so that is a good place to start.

- (Jan 12, 17) Outcomes and events:
- Key ideas
- Chapter 1.1-1.3 in Pitman
- Chapter 1.1-1.2 in Durrett
- Video lectures by Blitzstein Lecture 1: 14:30-End Lecture 3: 17:15-End
- Video lectures by Mattingly Outcome space and events, Partitions and rules of probability
- Extra problems: Drawing hearts Defective machines High card wins Taking classes Poker hands
- Homework: Assignment 1
- (Jan 19, 24) Conditional probability:
- Key ideas
- Chapter 1.4-1.6 in Pitman
- Chapter 1.3, 3.1, and 3.3 in Durrett
- Video lectures by Blitzstein Lecture 4 Lecture 5
- Video lectures by Mattingly Conditional probability Bayes rule Total probability
- Homework: Assignment 2
- (Jan 26, 31) Distributions I: Binomial, Poisson, Normal:
- Key ideas
- Chapter 2.1-2.4, 1.6 in Pitman
- Chapter 2.2-2.3, 3.2 in Durrett
- Video lectures by Blitzstein Lecture 8 Lecture 11 Lecture 13
- Video lectures by Mattingly Distributions Binomial I Binomial II Poisson approximation
- Homework: Assignment 3
- (Feb 2, 7) Distributions II: Hypergeometric, Multinomial, Counting:
- Key ideas
- Chapter 2.1, 2.5, 1.6 in Pitman
- Chapter 2.1, 2.3 in Durrett
- Video lectures by Blitzstein Lecture 2 Lecture 20
- Video lectures by Mattingly Counting 1 Counting 2 Geometric
- Homework: Assignment 4
- (Feb 9, 14) Random variables: Expectations, Variances, Moments:
- Key ideas
- Chapter 3.2-3.4 in Pitman
- Chapter 1.4-1.6 in Durrett
- Video lectures by Blitzstein Lecture 8 Lecture 9 Lecture 10
- Video lectures by Mattingly Continuous random variables Uniform random variables Scaling and standardizing
- Homework: Assignment 5
- (Feb 16, 21) Continuous random variables: Cummulative distributions, Probability densities, Change of variables, Order statistics:
- Key ideas
- Chapter 4 in Pitman
- Chapter 1.4, 5.1-5.3 in Durrett
- Video lectures by Blitzstein Lecture 14 Lecture 25
- Video lectures by Mattingly Uniform random variables Scaling and standardizing
- Homework: Assignment 6
- (Feb 23) Review
- (Feb 28) Exam 1: Histogram of results
- (March 2, 7, 9) Joint distributions: Marginals, Covariance, and Correlation
- Key ideas
- Chapter 5, 6.4, and 6.5 in Pitman
- Chapter 3.4, 5.4 in Durrett
- Video lectures by Blitzstein Lecture 19 Lecture 21
- Homework: Assignment 7
- (March 21, 23) Conditional distributions and expectations:
- Key ideas
- Chapter 6.1-6.3 in Pitman
- Chapter 5.5 in Durrett
- Video lectures by Blitzstein Lecture 25 Lecture 26 Lecture 27
- Homework: Assignment 8
- (Mar 28, 30) Law of large numbers:
- Key ideas
- Chapter 2.2 and 3.3 in Pitman
- Chapter 6.3 in Durrett
- Supplmental notes by Sayan
- Video lectures by Blitzstein Lecture 29
- Video lectures by Mattingly Binomial law of large numbers
- Homework: Assignment 9
- (Apr 4)) Review: Problems 2-7 and Solutions and Another exam
- (Apr 6) Exam 2 Histogram of results Mean: 42.5
- (April 11,13) Central limit theorem:
- Key ideas
- Chapter 2.2 and 3.3 in Pitman
- Chapter 6.1-6.6 in Durrett
- Supplmental notes Moment generating functions
- Video lectures by Blitzstein Lecture 30
- Video lectures by Mattingly Binomial central limit theorm Central limit theorm
- Homework: Assignment 10
- (April 18, 20) Markov chains:
- Key ideas
- Chapter in 4 Durrett
- Video lectures by Blitzstein Lecture 31 Lecture 32 Lecture 33
- (April 25) Review: Final and Solutions and Another exam and Another exam
- (May 2: 7-10pm) Final exam Histogram for Sta230 Histogram for Math230