EMSE 171/271 -
EMSE 4765/6765

Syllabus

Introduction

Course Files

Solutions

<< Courses Home Page

<< Home Page

DATA ANALYSIS FOR ENGINEERS AND SCIENTISTS:

Course Description:
A detailed statistical review is provided in the first four lectures. Topics that will be discussed include point estimation, confidence intervals, hypothesis testing and goodness-of-fit testing. These methods perform statistical inference in a single dimension (also known as univariate data analysis). Discussions of multivariate data analysis utilize matrices and vectors. One class will review rules of matrix-vector algebra and provides some intuitive geographical interpretations of these operations. Multivariate data analysis will be introduced by first discussing the classical Hotelling T2 hypothesis test, which is a natural extension of the univariate T test. Next, we introduce regression nalysis (in matrix-vector format), principal component analysis and analysis of variance. The introduction of these topics will be cursory and their application will be facilitated by the use of the MINITAB software program. Discussion of these multivariate techniques will concentrate on intuition, not a rigorous derivation of their methodologies.

Required Software:
MINITAB

Recommended Text Books:
"Analyzing Multivariate Data” by Lattin, Carroll and Green
"Probability and Statistics for Engineering and The Sciences” by Jay L. Devore