Announcements! ( See All )
10/8 Homework 7 posted. The calendar is subject to change pending campus decisions about cancellations.
10/1 Week 6 assignments have been posted. Midterm on 10/10 during lecture time.
9/25 Week 5 assignments have been posted.
9/17 Week 4 assignments have been posted.
9/10 Week 3 assignments have been posted. Quiz 1 Wed 9/11 in your assigned section.
9/3 Week 2 assignments have been posted. Quiz 1 will be on Wed 9/11 in your assigned section. See Piazza for info on Office Hours.
8/29 Welcome to the first lecture of Prob 140! We're excited to have you in this course. Discussion sections start tomorrow 8/30; please be sure to bring a laptop!

Material for the Midterm

Prob140 Fall 2019

A. Adhikari

The midterm is during the lecture time on Thursday October 10. 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, quizzes, and all the practice problems in the weekly Prep Guides.

Homework 6, due Tuesday October 8, consists of last semester’s midterm.

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