PREDICT 410: Predictive Modeling I Final Exam Study Guide
The final exam for PREDICT 410 will be administered in two parts: (1) a proctored exam
administered through Canvas and monitored by ProctorU, and (2) an unproctored take-home
exam administered thro

PREDICT 410: Predictive Modeling I Syllabus
INSTRUCTOR:
Winter 2016
William T. Mickelson, Ph.D.
william.mickelson@northwestern.edu
TEACHING ASSISTANT: Laurence Schneider
laurence.schneider@northwestern.edu
Course Description
This course develops the found

Principal Components Analysis with SAS
In this document we will outline the SAS procedures for performing principal components
analysis using the SAS procedure PROC PRINCOMP. In addition to the standard SAS
arguments, we will focus on the SAS options need

Summary of the linear regression component of Predict 410:
(1) Experienced the formulation of a typical data modeling project.
Every data modeling project starts with some data and a rough
problem, if you are lucky. Some data modeling projects start with

Introduction to Principal Components Analysis
1
What is Principal Components Analysis?
Statistical Interpretation - PCA is a transformation of a set of correlated random variables to a set of uncorrelated (or orthogonal) random
variables.
Linear Algebra

Factor Analysis with SAS
In this document we will outline the SAS procedures for performing the most common types of
factor analysis using the SAS procedure PROC FACTOR. By doing so, we will focus on calling
the correct SAS options to ensure that we are f

Estimation and Inference for Ordinary Least Squares Regression
1
Estimation - Simple Linear Regression
A simple linear regression is the special case of an OLS regression model
with a single predictor variable.
Y = 0 + 1 X +
(1)
For the ith observation

Statistical Inference Versus Predictive Modeling
in Ordinary Least Squares Regression
1
Introduction
There are two reasons to build statistical models: (1) for inference, and
(2) for prediction.
Statistical inference is focused on a set of formal hypoth

Statistical Assumptions for Ordinary Least Squares Regression
1
Introduction
In Ordinary Least Squares (OLS) regression we wish to model a continuous random variable Y (the response variable) given a set of predictor
variables X1 , X2 , . . ., Xk .
Whil

Analysis of Variance and Related Topics
for Ordinary Least Squares Regression
1
The ANOVA Table for OLS Regression
The Analysis of Variance or ANOVA Table is a fundamental output from a
tted OLS regression model. The output from the ANOVA table is used fo

Exploratory Factor Analysis
1
Introduction to Exploratory Factor Analysis
2
What is Factor Analysis?
Factor analysis is a statistical modeling technique used to model the
covariance structure in multivariate data.
Factor analysis is a statistical modeli