COURSE SYLLABUS

IE 201 ProbabIlITy and StatIstIcs I (3-0) 3

Catalog Data:

Introduction to statistics and descriptive data analysis. Probability. Random variables. Probability distributions. Mathematical expectation. Discrete and continuous probability distributions. Functions of random variables. Random sampling, data description, and some fundamental sampling distributions.

Textbook:

Walpole, R.E., Myers, R.H., and Myers, S.L., Probability and Statistics for Engineers and Scientists, 6th edition, Prentice-Hall, 1998.

References :

· Barnes, J.W., Statistical Analysis for Engineers and Scientists: A Computer-Based Approach, McGraw Hill, 1994.

· Hayter, A.J., Probability and Statistics for Engineers and Scientists, PWS Publishing Co., 1996.

· Papoulis, A., Probability and Statistics, Prentice-Hall, 1990.

· Vardeman, Stephen B., Statistics for Engineering Problem Solving, PWS Publishing Company, 1994.

· Montgomery, D.C., and Runger, G.C., Applied Statistics and Probability for Engineers, John Wiley and Sons, Inc., 1999.

· Moore, D.S., The Basic Practice of Statistics, W.H. Freeman and Company, 1999.

Prerequisites by Topic:

Differential and integral calculus, multiple integration.

Method for Assessing Student Knowledge of Prerequisite Topics:

A prerequisite exam will be given on prerequisite topics in the first two weeks.

Goals:

The course aims to expose students to basic concepts of probability and statistics to use basic modeling and statistical decision techniques in Industrial Engineering.

Objectives :

· To provide students a working knowledge of probability theory.

· To understand and apply basic concepts of probability theory to engineering problems.

· To understand the relationship between random variables and their distribution functions.

· To reinforce problem solving skills and to further student ability in analytical thinking.

Topics:

1. Introduction to statistics and data analysis (1 week)

2. Elements of probability theory (2 weeks)

3. Random variables and probability distributions (2 weeks)

4. Mathematical expectation (2 weeks)

5. Discrete probability distributions (2 weeks)

6. Continuous probability distributions (2 weeks)

7. Functions of random variables (1 week)

8. Random sampling, data description and some fundamental sampling distributions (2 weeks)

Laboratory Projects:

Laboratory assignments using MINITAB.

Contribution to Professional Component:

1. Mathematics and Basic Science 2 Credits

2. Engineering Science or Design 1 Credit

3. General Education 0 Credits