STAT 365 - Design & Analysis of Experiments

Credits: 3

This course will cover topics in design and analysis of experiments including analysis of variance (ANOVA) for single-factor design, randomized complete block design, Latin square design, balanced incomplete block design, two-factor factorial design and response surface, two-level factorial designs (2² and 2³), two-stage nested design and split-plot design.

In addition, associated model for each design - fixed effect model, random effect model, and two-factor mixed effect model will be discussed estimating model parameters, checking model adequacy, comparing contrasts using Scheffe’s method, comparing pairs of treatment means using both Tukey-Kramer and Fisher least significance difference (LSD) methods, estimating both variance components and intraclass correlation coefficient. A statistical software will be used.

Prerequisite(s): STAT 241

Term(s) Offered: Spring (even-numbered years)

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