Patrick Gurian's Webpage

Empirical Engineering Modeling and Inference

Spring 2006
Tuesday  6:00-8:50 p.m.
Revised 4/04/2006

Professor:  Patrick Gurian
Office:  Alumni Engineering 270-K
Phone: 215-895-2889

Office Hours:  Tuesday 4-5 and by appointment

Text:  Probability and Statistics for Engineers and Scientists, 6th Edition, by Jay L. Devore

Course Overview

This class covers empirical approaches to understanding engineering systems.  Students will learn to design experiments, develop statistical models, and use two common statistical software packages, SPSS and R.  Applications areas will include both environmental and civil engineering topics.

Course Policy
Students needing special accommodations for exams or coursework must submit letters in accordance with university policy.  Please turn off cell phones during class meetings.  Computers (any device with wireless connectivity or a full alpha-numeric keyboard) may not be used on exams.  Exams and quizzes can not be rescheduled because of prior travel arrangements.  If you have a conflict with either the final exam or midterm exam you should not enroll in this class.  Late assignments are penalized 3% per day late.  Homework assignments will routinely be announced by email and posted on WebCT.  Students are responsible for ensuring that they are on the class email list and for checking WebCT on a weekly basis.

Assignments (Grading)

Software Projects (20%)
Small projects will be assigned which will consist partly of documenting your results from the in-class activity and partly of extending the analysis and in some cases integrating your results with team members.  A hard copy must be turned in to the instructor in person, not by email, not left in a mailbox.  These will usually be due the week after they are assigned.

Quizzes (25%)
A quiz will typically be given at the start of class.  Each quiz will require about 10 minutes to complete.  The lowest quiz grade will be dropped.

Midterm (25%)
An exam will be given in class on during the 5th week of the term.

Final Project (30%)

Students will select a database to analyze during the course of the term.  The project will consist of an oral topic proposal in the 4th week of the term, an oral report in the 10th week, and a final report due during finals period.

Course Schedule




April 4

Review of hypothesis testing, p-values and confidence intervals

Chapters 7 and 8

April 11

Sample size calculations; Introduction to SPSS correlations and t-tests

Chapter 9

April 18

Chi-squared tests:  Introduction to R: an empirical proof of the Central Limit Theorem

Chapter 14

April 25

ANOVA;  Project topic presentations

Chapter 10

May 2

Midterm;  Maximum likelihood estimation, likelihood ratio tests, AIC, BIC

Chapter 6

May 9

Linear regression, correlation and causality,

Chapter 12

May 16

Multi-variate linear regression

Chapter 13

May 23

Logistic regression

Chapter 13

May 30

Statistical computing:  bootstrap methods


June 6

Project Presentations


June 15

Final Reports Due