Instructor:

Anil Aswani
4119 Etcheverry
Office hours – Tu 230-330P; Th 1130-1230p
aaswani [at] berkeley [dot] edu

GSI:

Matt Olfat
molfat [at] berkeley [dot] edu

Lectures:

TuTh 1230-200P, 105 North Gate

Discussions:

Section 1: W 4-5P, 3108 Etcheverry
Section 2: F 4-5P, 3106 Etcheverry

Website:

Optional Textbook:

Introduction to Probability and Statistics for Engineers and Scientists, by Sheldon Ross

Prerequisites:

IEOR 172 or STAT 134 or an equivalent course in probability theory

Grading:

Project (20%); homeworks (20%); midterm (20%); final exam (40%)

Midterm:

Tuesday, March 19, 2019   1230-200P

Final Exam:

Thursday, May 16, 2019   3-6P

Description:

This course will introduce students to basic statistical techniques such as parameter estimation, hypothesis testing, regression analysis, analysis of variance. Applications in forecasting and quality control.

Outline:

Specific topics that will be covered include:
  • Regression – Basic optimization; maximum likelihood estimation; least squares regression; high-dimensional regression; support vector machines (SVM's) (about 6 weeks)
  • Forecasting – ARAR algorithm; Holt-Winters algorithm; Holt-Winters seasonal algorithm (about 1 week)
  • Hypothesis Testing – Review of probability; t-test; confidence intervals; Mann-Whitney U test; multiple testing; ANOVA; Kruskall-Wallis test; likelihood ratio tests; quality control (about 6 weeks)

Lecture Notes:

Homeworks:

Feb 01
Homework 1 – Due Friday, February 15, 2019
(Solutions)
Feb 18
Homework 2 – Due Friday, March 1, 2019
(Solutions)
Feb 27
Homework 3 – Due Friday, March 15, 2019
(Solutions)
Apr 12
Homework 4 – Due Friday, April 19, 2019
(Solutions)
Apr 19
Homework 5 – Due Friday, April 26, 2019
(Solutions)
Z-Table and t-Table
Apr 29
Homework 6 – Due Friday, May 10, 2019
(Solutions)
Z-Table and t-Table

Project:

Mar 21
Course Project – Due Wednesday, May 8, 2018
winequality-red.csv
wholesale-customers.csv

Exam Solutions: