This is the course website for Winter 2020 Statistics class (170S). All information about homework, quizzes and exams will be posted here.


Some things to get started

Syllabus
Class time& room
MWF 4pm - 4:50pm, MS 5118
Textbook
Hogg, Tanis, Zimmerman Probability and Statistical Inference, 9th edition
Supplementary textbook: D. P. Bertsekas and John N. Tsitsiklis Introduction to Probability

My email
Liza Rebrova (rebrova@math.ucla.edu)
My office
6310MS
My office hours
M:5-6pm, W:3-4pm, F:5-6pm
TA
Ryan Wallace (rcwallace@math.ucla.edu)

Homework

Homework 1 and solutions
Homework 2 and solutions
Homework 3 and solutions and linear regression plot
Homework 4 and solutions
Homework 5 - due Feb 20
Homework 6 - due Feb 27

Supplementary material

First class presentation
Descriptive statistics (01/08) and a jupyter notebook if you'd like to play with the code
Quantile-quantile plot notes (01/10)
Linear regression example: here
Bayesian estimation, formulas and definitions: here
Spam filtering - bayesian classification example (01/27) and a jupyter notebook (data can be taken from this github repo)

PRACTICE MIDTERM; solutions and last problem solution /real midterm will have 40-50 points max/
Midterm review list
MIDTERM SOLUTIONS /typo in 1c and 1d: should be 10.6, not 10.4/