EG 390

Experiment Design and Analysis

In this course students learn how to design, evaluate, and implement experiments, and analyze the resulting data. The professional presentation and reporting of experimental results are addressed. Uncertainty analysis techniques are covered in detail. General uncertainty analysis is introduced as a means to evaluate a proposed experiment. Both the Taylor Series and Monte Carlo methods for estimating error propagation are covered. Hypothesis testing procedures for one-sample and two sample data comparisons are covered in detail. Factorial experiment design and analysis are also introduced. Students apply these theories in a final project.

Units: 3.0