Jason Newsom's
USP
654 Data Analysis II

Description
This
course takes an applied approach to statistical analysis and research
methodology and is the second in a twocourse sequence. The goal is to
provide students with statistical background, conceptual understanding,
technical writing skills, computer application, and the ability to apply
these skills to realistic data analysis problems and research designs. Topics
include simple regression and correlation, multiple regression, and logistic
regression. The laboratory (USP 654L) must be taken concurrently. Recommended
prerequisite: USP 634 Data Analysis or an equivalent course approved by the
instructor and prior experience with statistical software. All download files pdf unless otherwise noted. 

Fall 2014 Syllabus
Click
here
for the class syllabus, reading list, and my contact information.

Supplemental Readings
Click
here to download
readings in a zip file (9.1mb).

Current Homework
Get
a copy of the current homework.
Download homework
articles.

Homework Data Sets
Get the data you need here.

Exam
Reviews
Final
exam review sheet

Handouts and Overheads
(sorry,
not available until it has been covered in class, not all overheads included)
Overhead: Years
Since PhD and Publications Scatterplot
Overhead:
Exam and Time Scatterplot
Overhead:
Correlation Limitations
Simultaneous
Regression: SPSS Example
Hierarchical
Regression: SPSS Example
Overhead:
Good Hierarchical Table Example
Overhead:
Multiple Regression Venn Diagram
Overhead: Partial
and Semipartial Correlation
Partial and
Semipartial Correlation Example
Overhead:
Suppression Illustration
Coding of
Categorical Predictors and ANCOVA
Creating Indicator
Variables for Four Categories
ANOVA
and Regression Equivalence: Gender and Depression SPSS Example
Remedies for
Assumption Violations
Simple
Logistic Example with Binary Predictor
Simple
Logistic Example with Continuous Predictor
Link Functions and the
Generalized Linear Model
Regression Models
for Ordinal Dependent Variables
Ordinal
Logit and Probit Examples
Regression Models for
Count Data

SPSS Computer Lab
Handouts
and data, lab instructor: Peter Geissert
https://sites.google.com/a/pdx.edu/usp654ldataanalysis2labfall2013/ 
Stats Notes
Over 20 "Web
lectures" on introductory graduate statistics

Links
Jason's list of
statistics links
Jason's SPSS Macros for
Interactions and Simple effects
UCLA's statistical
computing site on SPSS
UCLA's
statistical computing site on regression with SPSS
Dave MacKinnon's
site on mediation
David Kenny's site (click on
"mediation")
Automatic calculator for calculating
significance of indirect effects
(compliments of Preacher & Leonardelli at KU and U of Toronto)
Bootstrap
Macros for calculating significance of indirect effects
(compliments of Hayes and Preacher at Ohio State & KU)