IE 331 Probability and Engineering Statistics
Core Course
2008 Course (Catalog) Description:
Descriptive statistics with graphical summaries. Basic concepts of probability and its engineering applications. Commonly used distributions for discrete and continuous random variables. Confidence intervals. Hypothesis testing. Correlation and simple linear regression.
Pre-requisite: Math203.
Text Book: STATISTICS FOR ENGINEERS AND SCIENTISTS William Navidi, 2nd Ed., 2008, McGraw-Hill
Higher Education, ISBN: 978-0-07-110222-3.
References:
1) Ronald E. Walpole, Raymond H. Myers, Sharon L. Myers and Keying Ye; Probability And Statistics For Engineers And Scientists 7th
Ed., 2002, Prentice Hall Inc, ISBN: 0-13-098469-8
2) Roxy Peck, Chris Olsen, Lay L. Devore; Introduction to Statistics and data Analysis, Duxbury Press, 2 ed., 2004, ISBN: 0534467105
3) William W. Hines, Douglas C. Montgomery, David M. Golsman, Connie M. Borror;
Probability and Statistics in Engineering, John Wiley & Sons, Inc., 2003.
Class Schedule:
This is usually multi-section classes and therefore different sections will have different schedules. Each section will meet either three times a week (1 hour duration) or two times a week (1 hour 20 minutes duration) and 2 hours of tutorial time.
Course Objectives:
At the end of the course the students will be able to:
1. Calculate the most important descriptive statistics.
2. Apply fundamental theories of probability.
3. Identify and calculate the statistics of discrete and random variables.
4. Apply some discrete and continuous probability distributions to real life problems.
5. Express statistical results graphically.
6. Perform confidence intervals calculations.
7. Perform statistical hypothesis tests.
8. Perform simple linear regression and correlation.
9. Use some statistical packages, and apply it to real world problems.
10. Interpret the obtained statistical results.
Topics covered during the class:
1: Sampling and Descriptive Statistics - Summary Statistics
- Graphical Summaries (2 weeks)
2: Probability
- Basic probability theories.
- Conditional Probability and Independence - Random Variables
(4 weeks)
3: Commonly Used Distributions - The Binomial Distribution - The Poisson Distribution - The Exponential Distribution - The Normal Distribution - The Central Limit Theorem - The Student's t Distribution (4 week)
4: Confidence Intervals (2 weeks) 5: Hypothesis Testing (1 weeks)
6: Correlation and Simple Linear Regression (2 weeks) Computer Usage: Excel, and Minitab.
