3 credits
Fall 2026 Lecture Distance Learning Upper Division
Introduction to statistical inference and experimental design. Correlation, regression, single and multi-factor ANOVA, non-parametric methods. Applications to statistical quality control.
Learning Outcomes1Use statistical software packages (e.g. Minitab) to perform statistical tests.
2Compute and interpret statistical confidence, tolerance, and prediction intervals given engineering and scientific data.
3Conduct and interpret parametric statistical tests (e.g. t-test, ANOVA) on engineering and scientific data.
4Conduct and interpret non-parametric statistical tests on engineering and scientific data.
5Conduct and interpret regression analysis on engineering and scientific data.
6Determine the appropriate statistical test or procedure to use on engineering and scientific data.
7Design basic factorial experiments and conduct basic statistical process control analysis.
Prerequisites
GPA by professor
made by Purdue students.