GSIA, 45-734
Carnegie Mellon University
Probability and Statistics II
Spring, 2001-2002 (mini 4)

Lectures section M: TR 6pm-7:50, GSIA 240
  section F: TR 8pm-9:50, GSIA 152
Instructor Bill Vogt
  HBH 2116D, 268-1843
Office Hours T 5:00-6:00
  R 5:00-6:00
Grader Amitabh Sinha,
Textbook Newbold, Paul (1995)
  Statistics for Business & Economics, 4th ed
  Upper Saddle River, NJ: Prentice-Hall
Software Eviews by Quantitative Micro Software

Course Objectives

Our objective will be to build understanding of the linear regression model and other advanced statistical tools.


This is the second course in a two course series in probability and statistics. The student is expected to be competent in algebra at the undergraduate level and to have successfully completed the first course, 45-733, or its equivalent.


The grade will be determined by performance on homework assignments, a midterm, and a final exam. Each will have equal weight. You are responsible for the content of the lectures, including any handouts, and chapters 12-15 in the text. The lectures cover material very similar to that presented in chapters 12-15 of the text.


We will use a general purpose statistical software package called Eviews, made by Quantitative Micro Software. The software is required. It will be used to generate class examples, to do homework, and to take the tests. It should already be installed on the laptops of MBA students. It is available online and at the campus computer store.

Various Class Policies

  1. Policy on Cooperation
  2. Policy on Aids During Exams
  3. Policy on Format of Assigned Work
  4. Policy on Lateness


The class schedule below is tentative and likely will not be followed exactly.

Date Material, Book Sections Work
T Mar 12 Introduction, Correlation, Regression (ch 12)  
R Mar 14 Ordinary Least Squares (ch 12)  
T Mar 19 Gauss-Markov Theorem, Estimation  
R Mar 21 Multivariate Regression (ch 13) HWK 1 due
T Mar 26 Multivariate Regression (ch 13)  
R Mar 28 Multivariate Regression (ch 13) HWK 2 due
T Apr 2 Spring Break, no class  
R Apr 4 Spring Break, no class  
T Apr 9 Dummy variables (ch 14) HWK 3 due
R Apr 11 Midterm - In class  
T Apr 16 Specification (ch 14)  
R Apr 18 Heteroskedasticity, Autocorrelation (ch 14)  
T Apr 23 Heteroskedasticity, Autocorrelation (ch 14) HWK 4 due
R Apr 25 Analysis of Variance (ch 15)  
T Apr 30 Analysis of Variance (ch 15) HWK 5 due
R May 2 Final Exam - In class  

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Russell W. Quong (
Last modified: Mar 4 2002