Instructor:
Anil Aswani
4119 Etcheverry
Office hours – Tu 10-11A; Th 230-330P
aaswani [at] berkeley [dot] edu
GSI:
Yonatan Mintz
4176B Etcheverry
Office hours – TuTh 3-4P
ymintz [at] berkeley [dot] edu
Lectures:
TuTh 11-1230P, 3106 Etcheverry
Discussions:
Section 1: F 10-11A, 310 Hearst Memorial Mining Building
Section 2: W 3-4P, 240 Bechtel
Website:
Optional Textbooks:
1.
Introduction to Probability and Statistics for Engineers and Scientists, by Sheldon Ross
2.
Introduction to Time Series and Forecasting, by Peter Brockwell and Richard Davis
http://link.springer.com/book/10.1007%2Fb97391
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 14, 2017 11-1230P
Final Exam:
Thursday, May 11, 2017 8-11A
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:
Discussion Notes:
Homeworks:
- Feb 02
- Homework 1 – Due Thursday, February 16, 2017
(Solutions)
- Feb 16
- Homework 2 – Due Thursday, March, 2, 2017
(Solutions)
- Mar 23
- Homework 3 – Due Thursday, April, 6, 2017
(Solutions)
- Apr 06
- Homework 4 – Due Thursday, April, 20, 2017
(Solutions)
Z-Table and t-Table
- Apr 20
- Homework 5 – Due Thursday, May 4, 2017
(Solutions)
Project:
Practice Questions:
Exam Solutions: