Jason T. Newsom PhD

Professor, Department of Psychology, Portland State University





Main Page


Current Courses

Univariate Quant

Multivariate Quant

Categorical Data Analysis

Structural Equation Modeling

Multilevel Regression

Psychological Measurement

Adult Development and Aging


Past Courses

Stats Notes



SEM References

SEM Books




LDA Book

Department of Psychology







Stats Notes


Stats Notes contains over 25 "Web Lectures," notes, and handouts on introductory graduate-level statistics. Topics range from sampling distributions to logistic regression (scroll down to get started)

This material was designed for a long distance course I taught many years ago and better updated material covers much of the same topics in more depth (Univariate Quantitative Methods and Multivariate Quantitative Methods)

The course was designed for Masters students with health backgrounds, and so the examples are often medical or biological in nature.

The statistical notation follows the author of the text used for the class (Wayne W. Daniel, Biostatistics, 7th Ed.) and is different from what I currently use in my courses or in other handouts on this site. It is probably healthy to be exposed to another notation system, even though it may be confusing if you have to use two systems at the same time.


There may be a few typos or other minor errors (what do you expect for free?).


Types of scales & levels of measurement

Sampling distributions

Significance testing

Sample Size

Normal and binomial probability distributions

Examples of Distributions and Descriptive Graphs

Between groups t-test

Example of between groups t-test

Within Subjects/Repeated Measures/Paired t

ANOVA (comparing two or more group means)

Within-subjects ANOVA

Chi-square: Goodness of fit and group differences when the dependent variable is dichotomous

Interactions and Factorial ANOVA

Graphs of main effects without interactions

Graphs of interactions with and without main effects

More on chi-square


Point-biserial correlation, Phi, & Cramer's V

Correlation and Causation

Simple Regression

R2 and tests of significance

Multiple Regression

More on Multiple Regression

Logistic Regression

Multiple Logistic Regression

Overview: A Hitchhiker's Guide to Analyses