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Jason Newsom's |
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About Stats Notes |
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§
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 a couple of years ago.
I no longer teach the course, but I teach a two-course sequence which
covers much of the same material in more depth §
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. This is a problem
with nearly all statistics textbooks—there is no standardized notation across
different authors. In the long run, 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. |
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Disclaimers
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I am not always right.
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There may be a few typos or other minor errors (what
do you expect for free?).
I would appreciate a brief note if you find any (newsomj@pdx.edu).
Web
Lectures
1/ Basic Concepts
Types of scales & levels
of measurement
Normal and binomial
probability distributions
Examples of Distributions and
Descriptive Graphs
2/
Differences Between Groups with Continuous Outcomes: t-tests
Example of between groups t-test
Within Subjects/Repeated
Measures/Paired t
3/
Differences Between Groups with Continuous Outcomes:
ANOVA
ANOVA (comparing two or more
group means)
4/
Differences Between Groups with Categorical Outcomes:
Chi-square
Chi-square:
Goodness of fit and group differences when the dependent variable is
dichotomous
5/
Complex Differences Between Groups: Factorial ANOVA and Multi-way Frequency
Tables
Interactions and Factorial
ANOVA
Graphs of main effects without
interactions
Graphs of interactions with
and without main effects
6/
Association Among Variables
Point-biserial
correlation, Phi, & Cramer's V
7/
Association and Prediction: Regression
8/
Association and Prediction: Logistic
9/
Overview
Overview: A Hitchhiker's Guide
to Analyses
Handouts
Handouts
are available for the following topics at the Data Analysis I and II sites.
(Sorry,
but handouts will be unavailable for topics yet to be covered during the
current session)
Data Analysis I: T-tests, Chi-square, ANOVA
Threats to internal validity
t-tests
Choosing the Correct Statistical Test
Contingency Chi-square
Post Hoc Tests
One-way ANOVA Definitional Formulas and Example
Factorial ANOVA Definitional Formulas and Example
Graphs of Possible Factorial Results in the Eyewitness
Example
Within-subjects ANOVA Definitional Formulas and Example
Assumptions for Within-subjects ANOVA
Mixed Factorial ANOVA
Data Analysis II: Regression and Logistic
Simple
Regression Hand Computation Example
Correlations
and Scatterplots (Lab 1)
Multiple Regression Example – Salary
Data
Hierarchical Multiple Regression Example—Salary Data
Suppression Example—Exercise Data
Coding of Categorical Predictors and ANCOVA
Coding Example for 4 Categories
Partial and Semipartial Correlation
SPSS Output
Remedies for Assumption Violations in Regression
SPSS Macro for Interactions and Simple Slope Tests
Simple Slope Tests Example Output
Mediation Analysis with Regression
Chi-square
Logistic Regression
More on Model
Fit and Significance of Predictors with Logistic Regression
Logit, Probit,
and Other Link Functions
Further