Engineering Applications of Statistics

Instructor: Conrad Fung

3 credits

Course Purpose

Most engineering decisions rely on numbers. But numbers in turn can be subject to variation, uncertainty, drift, bias, interpretation, context, unstated assumptions, and hidden agendas. The job of statistics is to find as much underlying truth as the numbers can reveal and to determine how much uncertainty remains. This course will teach you strategies for managing the uncertainty that exists in all numbers in order to maximize the chance that your decisions will be informed ones.

In the course, you will examine the structure of variation and learn the core descriptive methods for characterizing and comparing populations. You will also learn the more active tools of experimental design. As a final project you will design and execute a physical experiment and present the results.

You will use the MINITAB statistical package to carry out most of the analyses in the course.

Course Topics

  • Tracking Down Variation, Descriptive Statistics, and Statistical Software
  • Probability Distributions, Sample Size Effects, and Confidence Intervals
  • Comparing Two Means
  • Design of Experiments I, II, III
  • Measurement Capability, Variance Components, and Gage R&R
  • Regression Analysis I, II
  • Other Types of Data:¬† Skewness, Proportions, and Counts
  • Miscellaneous:¬† Survey Data and Process Capability Metrics
  • Project Preparation and Presentations