Jason's Main Page

Data Analysis I

Data Analysis II

SEM Class

MLR Class

Stats Notes


Statistical Links

Jason Newsom's
USP 654 Data Analysis II




This course takes an applied approach to statistical analysis and research methodology and is the second in a two-course 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 2015 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.



Handouts and Overheads
(sorry, not available until it has been covered in class, not all overheads included)


Overhead: Scatterplot Example

Correlation Example: SPSS and R

Levels of Measurement and Choosing the Correct Statistical Test

t-Tests, Chi-squares, Phi, Correlations: Its all the same stuff

Overhead: Simple Regression Variance Partitioning

Simple Regression Example: SPSS and R, Extra R Code

Overhead: Regression Plane

Overhead: Venn Diagram for Multiple Regression

Multiple Regression Example: SPSS and R

Hierarchical Regression Example: SPSS and R

Hierarchical Table Example I Like

Model Building Procedures

Overhead: Partial and Semipartial Correlation

Partial and Semipartial Correlation Example

Coding of Categorical Predictors and ANCOVA

Creating Coding Variables for Four Categories

Equivalence of ANOVA and Regression: SPSS and R, Extra R Code

Overhead: Diagnostic Plots

Darlington Suppression Example

Summary of Regression Diagnostics and Cutoffs

SPSS Regression Diagnostics Example (with tweaked data)

Regression Diagnostic Examples with R

Remedies for Assumption Violations and Multicollinearity

Curvilinear Regression Example: SPSS and R

Regression Moderation Examples: SPSS and R


Mediation Examples: SPSS and R

Review of Chi-square

Chi-square Example: SPSS and R

Logistic Regression

Simple Logistic Regression Using Continuous Predictor: SPSS and R

Computing the Odds Ratio from Cell Frequencies

Simple Logistic Regression with a Dichotomous Predictor: SPSS and R

Multiple Logistic Regression and Model Fit

Multiple Logistic Regression Example: SPSS and R

Link Functions and the Generalized Linear Model

Regression Models for Ordinal Dependent Variables

Ordinal Logit and Probit Examples: SPSS and R

Regression Models for Count Data

Further Readings




Computer Lab

Handouts and data, lab instructor: Jamaal Green




Stats Notes
Over 20 "Web lectures" on introductory graduate statistics




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)

R at the UCLA Idre site

David Gerbing's lessR manual

David Gerbing's lessR site

Oscar Torres-Reyna's Regression with R tutorial

Brief summary of some R regression related functions

Bootstrap Macros for calculating significance of indirect effects
(compliments of Hayes and Preacher at Ohio State & KU)

Carl Falk's mediation page (with R code links)

Mediation package for R

R for SAS and SPSS Users by Rob Muenchen