Contributing Scholar - Paul Joyce, University of Idaho

3 Semester Credit Hours

Course Description

The use of probability models and statistical methods for analyzing data has become common practice in virtually all scientific disciplines.  This course provides a comprehensive introduction to those models and methods most likely to be encountered and used by students in their careers in engineering and the natural sciences. 

Topics include basic concepts and rules of probability, random variables, probability distributions, expectation and variance, sampling and sampling distributions, statistical inference - estimation and tests of hypothesis, correlation and regression, and analysis of variance.

Prerequisites

• One year of college-level calculus 
• General prerequisite: Students must have the knowledge resulting from completing all coursework in the curriculum for a BS degree in engineering from an ABET-accredited engineering program in the United States or a CEAB-accredited program in Canada, or the equivalent from a foreign institution; performance level in this coursework should be equivalent to a cumulative undergraduate GPA of 2.9 or better on 4.0 scale
  

Course Objectives

Upon successful completion of this course, students should understand the role statistics plays in summarizing, reporting and rigorously establishing research findings; develop an appreciation for probabilistic and statistical reasoning; read texts, periodicals, and research journals with a greater understanding of statistical information presented; improve and refine problem solving skills, demonstrate a familiarity with using statistical features associated with various computing packages.

Course Topics

The following topics will be covered in the order given.

• Basic probability
• Conditional probability
• Independence
• Discrete random variables
• Binomial distribution
• Continuous random variables
• The normal distribution
• Jointly distributed random variables
• Covariance and correlation
• One sample inference-interval estimation
• One sample inference-hypothesis testing
• Two sample inference
• Analysis of variance
• Regression

Textbooks

Required: Probability and Statistics for Engineering and the Sciences, Jay L. Devore, Thomson Learning, 7th edition, ISBN 0-495-38217-5

Optional: Student Solutions Manual for Devore's Probability and Statistics, Matthew A. Carlton, Thomson Learning, 7th edition, ISBN: 0-495-38219-1

Disclaimer: The course syllabus may differ slightly from this course. Descriptions will be provided in your online course. Textbook information is provided only to give more information about the course.  Do Not use this information to purchase a textbook.  Up-to-date information will be provided when you register.