3 credits
Spring 2026 Lecture Distance Learning Upper Division
Fundamentals, completely randomized design; randomized complete blocks; latin square; multi-classification; factorial; nested factorial; incomplete block and fractional replications for 2n, 3n, 2m x 3n; confounding; lattice designs; general mixed factorials; split plot; analysis of variance in regression models; optimum design. Use of existing statistical programs.
Learning Outcomes1Understand design principles and use these principles to plan and implement an experiment in such a way that a statistical analysis results in valid and objective conclusions.
2Know how to choose an appropriate design given the available resources, factors of interest, and information on nuisance factors.
3Perform the proper statistical analysis and draw valid conclusions from any designed experiment.
Prerequisites
Restrictions
GPA by professor
made by Purdue students.