Download ISE 130 Course Syllabus

ISE 130: Engineering Probability and Statistics
Spring 2003
Instructor: Dr. Yasser Dessouky
485E Eng Building, 924-4133
Email:[email protected]
Office hours: MW 1:30-2:30,4-5:30
Objective:
To provide an introduction to the application of statistics in relation to engineering applications.
Pre-requisite: Math 32
COURSE CONTENT
1. Discuss, with many examples, the subjects of sample space, event, probability, probability
distribution, common discrete and continuous probability distributions, conditional probability
distribution, probabilistic modeling, etc..
2. Demonstrate the meaning and power of the Central Limit Theorem, the Law of Large Numbers, etc..
3. Introduce the fundamentals of Engineering Statistics, including charting, interpreting, and analyzing
the data; statistical hypothesis testing; estimation of the parameters of a probability distribution
(point estimation and confidence interval).
Textbook:
Applied Statistics and Probability for Engineers, Montgomery and Runger, Wiley.
Grading:
Homework
Exams (2@25)
Final
Percent
20
50
30
Course Conduct
Homework assignments are to be completed individually and are due at the beginning of class on the
date specified. If you plan to miss class on a day an assignment is due, submit it ahead of time. Late
assignments will be penalized 20%. You have one week to turn in the assignment if it is late before you
receive no credit for the assignment. It is appropriate to ask another student for help in clarifying a point
in a problem you attempted alone. However, do not copy another student’s assignment nor allow another
student to copy your assignment. This is academic dishonesty.
In general, exams will be closed book and closed notes. Students will be allowed to bring in one 8.5” by
11” sheet with their own summarized material (commonly called a “cheat sheet”).
NO:



Cell phone and pager use during class
Chewing gum during class
Late arrival to class
Week
1
2
2,3
3
4
5
6
7
8
9
Chapter
1
6
2
2
3
3
4
4
7
7
9
7
10
11
8
9
12
9,10
13
10
14
15
16
Final
13
11
These Dates May Flex
Topics
Introduction to probability and statistics
Data Summary and Presentation
Probability; sample space; events
Conditional Probability; Independence
Discrete Random Variables and Distributions
Discrete Random Variables and Distributions
Continuous Random Variables and Distributions
Continuous Random Variables and Distributions;
Random Sampling; Sampling Distributions
Parameter Estimation; Estimators
Sum and Average of Random Variables;
Central Limit Theorem; Law of Large Numbers
Confidence Interval
Application of Parameter Estimation and Hypothesis Testing:
Statistical Inference for One Sample
Application of Parameter Estimation and Hypothesis Testing:
Statistical Inference for One Sample and Two Samples
Application of Parameter Estimation and Hypothesis Testing:
Statistical Inference for Two Samples
Analysis of Variance
Linear Regression
Review
Friday, May 16 12:15-14:30