CS/SE 3341 Probability and Statistics in Computer Science

MW 700 - 815 pm in ECSS 2.306

Fall 2009
Instructor: Michael Baron
Office: ECSN 3.912
Phone: 972-UTD-6874
Office hours: TBA
Text: Trivedi. Probability and Statistics with Reliability, Queuing, and Computer Science Applications, Wiley, 2nd ed.
List of errors in this textbook

Syllabus - schedule, grading policy, tips, contacts

eLearning - check your grades and join discussion groups


Homework

Homework 1 - preparation for Quiz 1. Quiz 1 "Probability Rules. Independence" is on September 9
Homework 2 - preparation for Quiz 2. How do you like this Bayesian calculator? Quiz 2 "Conditional Probability. Bayes Rule" is on September 16
Homework 3 - preparation for Quiz 3. Quiz 3 "Random variables and random vectors" is on September 23
Homework 4 - preparation for Quiz 4. Quiz 4 "Discrete distributions: Bernoulli, Binomial, Geometric, Negative Binomial, and Poisson" is on September 30
Homework 5 - preparation for the Midterm Exam
Homework 6 - preparation for the Midterm Exam
Homework 7 - preparation for Quiz 5. Quiz 5 "Expectation and variance. Central Limit Theorem" is on October 28.
Homework 8 - preparation for Quiz 6. Quiz 6 "Binomial and Poisson processes" is on November 4
Homework 9 - preparation for Quiz 7. Quiz 7 "Markov chains" is on November 11
Homework 10 - preparation for Quizzes 8 and 9
             Quiz 8 "Binomial Single-Server Queuing System" is on November 18
             Quiz 9 "M/M/1 Queuing System" is on November 25

The Final Exam is on Monday, December 14, 7-9 pm. Here is Practice Final

Quizzes and Exams

Quiz 1, solutions.
Quiz 2, solutions
Quiz 3, solutions
Quiz 4, solutions
Midterm Exam, solutions
Quiz 5, solutions
Quiz 6, solutions.
Quiz 7, solutions.
Quiz 8, solutions

GRADES ARE HERE.
Learn how to manage exam stress.

Some Lecture Notes

(You may need Acrobat Reader to see and print these notes)

Notes 0 "Introduction to this course"
Notes 1 "Introduction to Probability. Set operations. Basic rules of Probability"
Notes 2 "Equally likely outcomes. Conditional probability"
Notes 3 "Random variables and distributions"
Notes 4 "Discrete distributions"
Notes 5 "Continuous distributions"
Notes 6 "Important continuous distributions"
Notes 7 "Expectation, variance, and Central Limit Theorem"
Table of Normal distribution (without typos)
Notes 8 "Computer simulations and Monte Carlo methods"
Notes 9 "Stochastic processes. Bernoulli, Binomial, Poisson processes."
Notes 10 "Markov chains"
Notes 11 "Single-server queuing systems"
Notes 12 "Statistical inference"


Matlab corner

  • MATLAB programs used in various classroom demonstrations:
    Markov chain for sunny and cloudy days
    Markov chain for the game of ladder
    Poisson process of arrivals
    Bernoulli and Binomial processes
    Brownian motion
    Central Limit Theorem
  • A Matlab tutorial
    Any questions/comments/suggestions? Write to mbaron@utdallas.edu