Overview

This course covers fundamentals of experimental design, analysis of categorical data, the general linear model, and regression. Students will learn how to set and analyze experiments using basic experimental design starting with two-sample methods and advancing to designs such as factorials, fractional factorials, and randomized block designs. Designs appropriate for human research (such as repeated measure designs) and /or large scale simulation experiments (such as Latin hypercube designs) are included. Parametric and nonparametric approaches are compared and contrasted. Datasets and motivational examples are drawn from recent research relevant to HSI and/or MOVES. 

Included in Degrees & Certificates

• 359

Prerequisites

• OS3111
• College Algebra

Learning Outcomes

At the completion of this course, students will have a foundation in experimental design, working knowledge of various statistical methods, and familiarity with different types of statistical software.  Students will:

• Understand the practical aspects of experimental design.
• Recognize the appropriate statistical method based on the design and research question.
• Develop skills in using typical statistical software and interpreting the output.
• Recognize different experimental design approaches and their strengths and limitations.
• Develop a working knowledge of methods for assessing the fit of a model.