Announcements! ( See All )
4/28 - Final Assessment Part I has been released, and is due Tue 5/5 at 12PM noon.
4/21 - Week 13 Checkpoint, HW 12, and Lab 9 have been released. Week 13 Checkpoint is due Thu 4/23, HW 12 is due Tue 4/28, and Lab 9 is due Sun 5/3.
4/14 - Week 12 Checkpoint and HW11 have been released. Week 12 Checkpoint is due is due Thu 4/16, and HW 11 is due Tue 4/21
4/7 - Week 11 Checkpoint, HW 10, and Lab 8 have been released. Week 11 Checkpoint is due Thu 4/9, HW 10 is due Tue 4/14, and Lab 8 is due Sun 4/19.
3/31 - Homework 9 and the Week 10 Checkpoint have been released. Week 10 Checkpoint is due 4/2 and Homework 9 is due 4/7.
3/20 - Homework 8 and Lab 7 have been released. Homework 8 is due Tue 3/31 and Lab 7 is due Sun 4/5.
3/10 - Homework 7 and Lab 6 have been released. Homework 7 is due Tue 3/17 and Lab 6 is due Sun 3/15.
3/5 - Homework 6 has been released, and is due Tue 3/10. No Lab this week.
2/25 - Lab 5 has been released, and is due Sun 3/1. No Homework this week so you have time to study for the Midterm on Tue 3/3.
2/18 - Homework 5 has been released, and is due Tue 2/25. Lab 4 is due Sun 2/23.
2/11 - Homework 4 and Lab 4 have been posted! Lab 4 is due Sun 2/23. This is a challenging lab; please start early. Lab Party on Thu 2/13 is being converted to a Homework Party.
1/21 - Homework 1 and Lab 1 have been posted! First section Wed 1/22, please be sure to bring a laptop!

Material for the Midterm

Prob140 Spring 2020

A. Adhikari

The midterm is during the lecture time on Tuesday March 3. This is a summary of the material for the exam, grouped by main topic. The general techniques are in the sections Probability, Distribution, and Expectation. The next two sections consist of applications.

The labs relevant to the midterm are listed below by topic. Please also review all your homework, Quiz 1, and all the practice problems in the weekly Prep Guides.

Probability

  • Chapter 1: Spaces, events, basic counting, exponential approximation
  • Chapter 2: Addition and multiplication rules, conditioning and Bayes’ rule
  • Chapter 5: Unions and intersections of several events
  • Section 9.1: Probabilities by conditioning and recursion

Distribution

  • Chapter 3: Random variables, equality versus equality in distribution
  • Chapter 4: Joint, marginals, conditionals, independence
  • Section 5.4: Random permutations and symmetry

Expectation

  • Chapter 8: The main properties, including additivity, the method of indicators, and expectations of functions, and tail sum formula for the expectation of a non-negative integer valued variable
  • Lab 3: Application of tail sum formula
  • Sections 9.2, 9.3: Expectation by conditioning
  • Lab 4: Waiting times till patterns: application of expectation by conditioning

Random Counts

  • Section 8.1: Bernoulli
  • Section 8.1: Uniform on a, a+1, … , b
  • Sections 6.1, 6.2, 6.4, 7.2: Binomial and multinomial
  • Sections 5.4, 6.3, Lab 1: Hypergeometric
  • Section 6.5, Chapter 7: Poisson
  • Sections 8.1, 9.3: Geometric

Markov Chains

  • Sections 10.1, 10.2: Terminology and basics
  • Sections 10.3, 10.4: The steady state distribution and its properties
  • Section 11.1, 11.2: Detailed balance
  • Sections 11.3, 11.4: Code Breaking and MCMC