{[ promptMessage ]}

Bookmark it

{[ promptMessage ]}

SYLLABUS_EMSE%20171_271

# SYLLABUS_EMSE%20171_271 - Syllabus EMSE 171/271 Department...

This preview shows pages 1–2. Sign up to view the full content.

Department of Engineering Management and Systems Engineering School of Engineering and Applied Science Syllabus: EMSE 171/271 Semester: Fall 2008 Page 1 of 4 EMSE 171/271 – Data Analysis for Engineers and Scientists Instructor Information: Dr. J. Ren é van Dorp - Professor Office Address: 1776 G Street, Office 135, Washington DC 20052 Telephone Number: 202-994-6638 Fax Number: 202-994-0245 E-mail: [email protected] Office Hours: Tuesday 1:00PM to 3:00PM 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). Discussion of multivariate data analysis requires the introduction of matrices and vectors. One class will review rules of matrix-vector algebra and provides intuitive geographical interpretations of these operations. Multivariate data analysis will be introduced by first discussing the classical Hotelling T 2 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 (ANOVA). 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. Prerequisite Requirement: ApSc 115: Engineering Analysis III (or any other undergraduate Applied Statistics course from a physical or natural sciences program). Course Objectives: Each student should: (1) Get a solid refresher on classical statistical inference techniques, (2) become familiar with matrix-vector operations, (3) get an intuitive feel for a variety of multivariate

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}

### Page1 / 4

SYLLABUS_EMSE%20171_271 - Syllabus EMSE 171/271 Department...

This preview shows document pages 1 - 2. Sign up to view the full document.

View Full Document
Ask a homework question - tutors are online