Course Detail
Units:
3.0
Course Components:
Lecture
Enrollment Information
Enrollment Requirement:
Prerequisites: 'C' or better in (ME EN 2550 OR MATH 3070) AND Full Major status in Engineering.
Description
The purpose of this course is to introduce mathematical concepts and statistical methods used in modern engineering problem solving and analysis. The goal is to introduce students to analytical and numerical tools to design experiments to effectively and efficiently solve real-world engineering problems. Lectures will be supplemented by several programming exercises using R, and a large number of practical examples on relevant engineering topics related to design of experiments and data analysis. The use of experimental designs is a prescription for successful application of the scientific method. The scientific method consists of iterative application of the following steps: (1) observing a selected state, (2) hypothesizing the mechanism for what has been observed, then (3) collecting data, and (4) analyzing data to draw valid conclusions. Statistical experimental designs provide a plan for collecting data in a way that they can be analyzed statistically to corroborate the hypothesis in question. This is an organized approach which helps to avoid false starts and incomplete or invalid answers to research questions.