MAT 245 - Design of Experiments
This course is an introduction to the most common types of statistical designs and analyses of experiments. Topics include single-factor experiments with randomized blocks, Latin squares, incomplete blocks, two-factor experiments, 2^k designs, fractional designs, response surface techniques, and other selected topics. Technology will be used throughout the course.
Prerequisite: MAT 224 Statistics II or MAT 260 Applied Probability and Statistics
3 Class Hours
Learning Outcomes of the Course:
Upon successful completion of this course the student will be able to:
1. Determine an appropriate design to fit the analysis.
2. Test hypotheses with contrasts.
3. Analyze an experiment using completely randomized designs, complete block designs, incomplete block designs, Latin square designs.
4. Develop and analyze factorial designs.
5. Use response surface methods.
6. Use nested design and covariance design.
7. Use technology for design and analysis of experiments.
In the context of the course objectives listed above, upon successful completion of this course the student will be able to:
1. Interpret and draw inferences from mathematical models such as formulas, graphs, tables and schematics.
2. Represent mathematical information symbolically, visually, numerically and verbally.
3. Employ quantitative methods such as arithmetic, algebra, geometry, or statistics to solve problems.
4. Estimate and check mathematical results for reasonableness.
5. Recognize the limitations of mathematical and statistical methods.
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