School of Information and Computer Science
Department of Statistics

Math 67 - INTRODUCTION TO PROBABILITY & STATISTICS

Class Info
Gang Liang
346G Computer Science
949-824-9795 (o)
liang@uci.edu
Office hours: MWF 2:45-4pm or by appointment

TA: My An Tran (mtran@math.uci.edu)
Office hours: Wed 1-2pm and Th 8-9am

Lecture: MWF 4:00-4:50pm @ MSTB 120

Discussion: TuTh 4-4:50pm @ Social Science Trailer 220A

Participation: Extra credits will be given for participation in class email discussions: asking and answering questions.

Grading: The final grade will be 10% participation credit plus the better between: a) 20% homework, 30% midterm exam, 40% final exam, and b) 90% final exam.

You are required to take most of the homework and midterm exams in order to use part b). The university-wide principles of academic honesty and integrity are enforced.
Misc Links
Textbook   Introduction to Probability and Statistics,
4th Edition, by J.S. Milton, J.C Arnold


Mailing list   44503-S05@classes.uci.edu, archive, FAQ

Grades   http://eee.uci.edu/toolbox/gradebook

While writing my book [Stochastic Processes], I had an argument with Feller. He asserted that everyone said random variable and I asserted that everyone said chance variable. We obviously had to use the same name in our books, so we decided the issue by a stochastic procedure. That is, we tossed for it and he won. -- Doob, J.L.
Class Schedule
Week 01   (1.2, 2.1) sample space, addition/multiplication rules, axioms of probability, discrete uniform law
Week 02   (1.3, 2.2, 2.3, 2.4) counting (permutation, combination), conditional probability, independence of events, Bayes's theorem, random variables
Week 03   (3.1-3.2) Uniform, Bernoulli, binomial, mean and variance (discrete), model and distribution parameters
Week 04   (3.4-3.8) some important discrete distributions: Poisson, geometric, a midterm
Week 05   (4.1-4.4) continuouse random variables (mean and variance), density, cdf function, normal, chi-square, Gamma distribution
Week 06   (5.1-5.3) joint/marginal distribution, independent, covariance, conditional expectation
Week 07   (4.8, 5.5) transformation of variables, a review session, and a midterm
Week 08   (6.1, 6.3) random sampling (with or without replacement), sample mean and variance, parameter estimation
Week 09   (7.1-7.3) point estimation, maximum likelihood, and method of moment (brief)
Week 10   (7.4) central limit theorem and law of large number, all questions answered
Quizzes and Exams
Homework 1, Due April 13 (Wed), solution
Homework 2, Due April 20 (Wed), solution
Homework 3, Due April 27 (Wed), solution
Homework 4, Due May 11 (Wed), solution
Homework 5, Due May 18 (Wed), solution
Homework 6, Due June 1 (Wed), solution
Homework 7, Due June 8 (Wed), solution

Last Modified: Monday, 11-Jul-2005 13:41:59 PDT by Gang Liang.