Engineering Statistics and Quality Control

Catalog description

This is a first course in statistical practice, targeted to engineering students. Topics include basic probability, random variables and probability distributions, statistics and sampling distributions, maximum likelihood estimation, (one- and two-sample-based) hypothesis testing and interval estimation, quality control, principal components and canonical correlation analysis, statistical modeling and learning concepts, exploratory data analysis, linear and logistic regression models, one-way analysis of variance (ANOVA), and an introduction to machine learning. The course focuses on context, concepts, analytic problem solving, and numeric applications, and not on statistical theory. All numeric work will be performed using the Python programming language. Prerequisites: ( 21-112 or 21-120 ) and ( 02-120 or 15-110 or 15-112 )