INTRODUCTION TO INDUSTRIAL STATISTICS
Introduction to basic probability and statistical tools and methods from an industrial application perspective. Random variables and probability distributions; descriptive statistics; point estimates. Perform hypothesis testing, construct confidence intervals, and understand design of experiments in the context of motivating case studies. Regression and correlation analysis. Focus on applying statistical methods and tools to solve engineering problems. Use of Microsoft Excel to interpret and analyze data.
Prerequisites & course information
Requisites: ( MATH 211 , 217, or 221 ) or member of Engineering Guest Students Course Designation: Core GenEd - Mathematics & Quantitative Reasoning Repeatable for Credit: No Last Taught: Fall 2026 Learning Outcomes: 1. Articulate the importance of statistics in engineering applications Audience: Undergraduate 2. Summarize and describe data using descriptive statistics and graphical methods Audience: Undergraduate 3. Perform basic statistical analysis on datasets Audience: Undergraduate 4. Design simple experiments with data for the purpose of statistical analysis Audience: Undergraduate 5. Use Excel to describe, analyze, graph, and interpret data Audience: Undergraduate 6. Apply linear and multiple regression techniques Audience: Undergraduate 7. Apply experiment and analysis techniques to areas of engineering such as Statistical Process Control Audience: Undergraduate 8. Apply basic probability concepts such as random variables, independence, and probability distributions Audience: Undergraduate Learning Outcomes: 1. Articulate the importance of statistics in engineering applications Audience: Undergraduate 2. Summarize and describe data using descriptive statistics and graphical methods Audience: Undergraduate 3. Perform basic statistical analysis on datasets Audience: Undergraduate 4. Design simple experiments with data for the purpose of statistical analysis Audience: Undergraduate 5. Use Excel to describe, analyze, graph, and interpret data Audience: Undergraduate 6. Apply linear and multiple regression techniques Audience: Undergraduate 7. Apply experiment and analysis techniques to areas of engineering such as Statistical Process Control Audience: Undergraduate 8. Apply basic probability concepts such as random variables, independence, and probability distributions Audience: Undergraduate
Sources
- Course catalogue ↗2026-2027