Northwestern University

Department of Industrial Engineering and Management Sciences IEMS 303: Statistics I (Winter 2011)

Instructor: Professor Bruce Ankenman Office: Tech C138, Tel: 491-5674

email: ankenman@northwestern.edu Office Hours: Tues 2:30-3:30

T. A.: Paul Pei peipauj@northwestern.edu, Office Hours: TBD

Lecture: MWF 10:00-11:00, M152

Discussion Section: Although it is scheduled in Caesar, the discussion session is not

used.

Prerequisite: A previous course in probability at the level of IE 202.

Texts: 1. “Probability and Statistics for Engineering and the Sciences” by Jay L.

Devore, 7th

Edition enhanced, Brooks/Cole – Thompson, 2004, Belmont, CA.

Syllabus: 1. What is Statistics? (Ch. 1)

2. Data Summary and Presentation (Ch. 1)

3. Sampling Distributions, Estimation (Ch. 5&6)

4. Confidence Intervals for a Single Sample (Ch. 7)

5. Testing for a Single Sample (Ch. 8)

6. Confidence Intervals and Testing for Two Samples (Ch. 9)

7. Linear Regression and Correlation (Ch. 12)

8. Introduction to Multiple Regression (Ch. 13)

9. Factorial Experiments (handout)

Grade: Homework 15%, Midterm 20%, Labs 15%, Final 30%, Project 20%.

Homework: Homework problems will be assigned every week on Friday. They are to

be handed in on the next Friday AT THE BEGINNING OF CLASS. Late

homework will have a 20% reduction. Homework that is more than one class period

late receives no credit. We will not grade the homework in detail since the answers

are in the back of the book or will be given. However, you will not receive credit for

problems where insufficient work is shown.

Exams: There will be a 2-hour midterm held in an evening to be determined later. The

exams are closed book, but you may bring a copy of the tables from the back of the

text; on the backs of these pages you can make any notes or write formulas that you

need. The final will be comprehensive.

Lab: There will be 2 laboratories-each of which has a project report due. All labs will be

done in teams of 4, and teams will need to sign up for 1.5 hours of lab time in Tech

C125 for each lab. The lab report should have four sections (1) Introduction, (2)

Methods, (3) Analysis section and (4) Conclusions. Give explicit answers to the lab

questions in the Analysis section and put the most useful graphs and Minitab output

in this section for easy reference. An Appendix should contain the raw data, and any

other graphs or Minitab output that you want to attach, but was not critical enough to

put in the Analysis section. The report should be 2-4 pages excluding the Appendix.

Project: For the project, you will be working in the same teams of 4 as for the labs. You

will choose a research question, formulate it as a hypothesis testing or estimation

problem, collect the necessary data from existing sources or by doing a small survey

or experiment, analyze the data graphically and by using formal statistical techniques

and write a report not to exceed 10 pages of text (exclusive of any appendices). The

lab report should have four sections (1) Introduction, (2) Methods, (3) Analysis

section including a subsection “Limitations of this Study,” and (4) Conclusions. Put

the most useful graphs and Minitab output in the Analysis section for easy reference.

An Appendix should contain any graphs or Minitab output that you want to attach,

but were not critical enough to put in the Analysis section. Please send me an e-

copy of the raw data. A project proposal not to exceed 1 page with the team

member’s names is due on Friday, January 21. The final project reports are due on

Friday, March 11 in class. The best projects are always ones where you answer

some question that you (or some client) can use to make a decision that requires data

collection and analysis. Some examples of possible project topics are:

a) Take two competing products or processes (e.g. Tide and Cheer, Walk

or Take shuttle) and conduct a randomized experiment to compare

them. Design your study with sufficiently large sample size to detect

any practically significant true difference.

b) Suggest a change for improving the performance of some system (e.g.

Increase sleep hours before taking tests). The change should be easily

implementable. Collect data before and after the intervention and

compare the results.

c) Use archival data to answer a public policy question such as (1) Does

lowering the speed limit reduce traffic accidents? (2) Do stricter gun

laws reduce violent crimes? Discuss the difficulties of drawing

conclusions from archival data.

Teammate Evaluation: Each person will fill out an evaluation form at the end of the

quarter to rate how their teammates participated in the labs and project. This is to make

sure work is shared fairly. The form is posted on Blackboard.

Availability of MINITAB: MINITAB is available in the IE/MS Computing Lab in Tech

C135. It is also available for a low-cost trial basis on e-academy.com