Probability and Statistics for Engineers

STA 4032, Spring 2011

Class meets: ED 120, 10:00-10:50AM MWF

Instructor: Dr. Lianfen Qian, email: lqian@fau.edu Prerequisites: MAC 2312

Office Hours: 11:00-12:00Noon, MWF SE 244 or by appointment

Course Description:

Basic concepts of probability; random variables; discrete and continuous probability

distributions; estimation theory; tests of hypotheses; error analysis.

Goal (outcomes): Student should be able to manipulate data, familiar with various statistical

distributions, and have the ability to translate to information. Understand central

tendency and variability. Be able to perform hypothesis testing. Be able to carry out

error analysis.

Textbook: Applied Statistics and Probability for Engineers, 5th

Ed. by Douglas C. Montgomery

and George C. Runger. 2011. ISBN: 978-0-470-05304-1. Grading system: Two Midterm Exams (TBA) 20% each for 40%

Three Quizzes 30%

Final Exam 30%

Course Webpage: Blackboard will be used for course information and documentation, and

communications.

Holidays: Jan. 17, March 7-13.

Attendance: The instructor reserves the right to make any changes she considers academically

advisable. Note that it is your responsibility to attend the class and keep track of the

proceedings.

Tentative Schedule

Wk Ch Topics

1 1, 2 Introduction, models, probability distributions, joint and conditional

probability, marginal probability

2 2, 3 Bayes' theorem, random variables, independence, discrete random variables,

cumulative distributions, expected value, binomial, geometric,

negative binomial distributions

3 3, 4 Quiz 1: Chapters 1 and 2 Discrete random variables: hypergeometric distribution, Poisson distribution;

continuous random variables: probability density functions,

cumulative distribution, expected value

4 4 Continuous random variables: Normal, normal approximation to binomial

and Poisson, exponential, Weibull

5 5 Joint, marginal, conditional probability distributions

Midterm 1: Ch 1-4

6 5, 6 Covariance and correlation, bivariate normal, linear combinations of random

variables, data description, graphical display

7 7 Random sampling, estimators, maximum likelihood, least squares,

moments, sampling distributions

8 8 Quiz 2: Ch 5, 6 Confidence intervals, t distribution

9 9 Hypothesis testing; single sample tests: mean, variance, proportion;

chi-square distribution

10 9 Goodness-of-fit, contingency tables

Midterm 2 Ch 5-9.6

11 10 Two-sample tests of means, proportions, F-distribution

Two-sample test of variance

12 11 Simple linear regression, point estimation

13 11,

12

Quiz 3: Ch 9.7-10.3

Confidence intervals and tests for simple linear regression

14 Error analysis

(Lecture notes)

15 13 Single-factor ANOVA

16 May

2

7:45 – 10:15 AM Final Exam: 9.7-13 and error analysis