Applied Multivariate Analysis

STAT 460, Spring 2015

Darren Homrighausen

Syllabus


Lecture:

Date and Time: Monday, Wednesday, Friday from 10:00 - 10:50 pm
Location: Engineering 101 B

Office hours: Tuesday 11:00am or by appointment, Statistics 204
TA: Paul Harmon: email (use R) paste(c(paste(c('paul','harmon','gj'),collapse=''),'gmail.com'),collapse='@')


Applied Multivariate Analysis involves a good deal of both applied work (programming, problem solving, data analysis) and theoretical work (learning, understanding, and evaluating methodologies). We will try to make the class as applied as possible. However, there are necessary detours into the more technical aspects.


Project:

Project Outline

Homeworks:

HOMEWORK 1
HOMEWORK 2
HOMEWORK 3
HOMEWORK 4
HOMEWORK 5
HOMEWORK 6
HOMEWORK 7
HOMEWORK 8
HOMEWORK 9
HOMEWORK 10
HOMEWORK 11 (r code)

Lectures:

R Tip 'o the Day

PRELIMINARY MATERIALS

REGRESSION CLASSIFICATION DERIVED INPUTS
  • PCA
    • [Updated: Mar. 20, 10:00 AM, Mar. 24, 4:30 PM]
  • PCA applications
    • [Updated: Mar. 24, 4:30 PM, Mar. 26, 9:30 PM, Mar. 30, 11:00 AM]
CLUSTERING FACTOR ANALYSIS TEXT PROCESSING

Test materials:
Midterm ideas
Midterm


R-project Materials: