# Advanced Statistics

**Advanced Statistics**

**Advanced Statistics**

This course is designed to be an intensive investigation into statistical analyses commonly used in Psychology and other social-behavioral sciences. Topics include Factorial ANOVA, Repeated Measures, Multiple Regression, Trend Analysis, Non-Parametric procedures, and the General Linear Model (GLM).

In addition, the student will be exposed to various analytic philosophies. The course will be computer intensive (using SPSS). Students are expected to be familiar with basic statistical issues, though they will be reviewed at the beginning of the class.

The main goals of this course are to: (a) expose the student to advanced statistical techniques, (b) make the student proficient in the techniques, (c) give the student the expertise to â€śthinkâ€ť about appropriate statistical techniques for the problems they will face in and out of academic settings, and (d) give the student exposure to different analytic strategies and philosophies. This course is associated with select student-learning objectives (linked to Program Goals), including writing skills, critical analysis of research, research skills, applying knowledge to real world problems/applications, and working with others.

This course is analysis and writing intensive. Students usually spend approximately 5-10 hours per week on homework assignments beyond class time.

(Summer 2013)

(Spring 2013)

(Fall 2012)

PLEASE NOTE: The example data here is taken from the Thursday stats section of my statistics class during the Fall semester of 2012. The actual data in these examples may differ slightly from the data used in your class. Similarly, the syntax matches the data used in *their* class -- you may need to adjust the name of the variable *slightly* to match the names used in your class *per se*. If you were in the Thursday stats class from fall of 2012, you're in luck -- this is exactly what you saw in class.

ALSO, please note that prior to Fall of 2012, Argosy always started the school year on a Monday, so classes that meet twice during the week starts on Thursday. This means that an academic week on this calendar runs from Thursday to Wednesday. That means that for the week of Thanksgiving, it reads "No Class." However, there is no class for the Thursday class, but there is class for the Tuesday class, and they are still finishing up their week.

This class was originally taught using the SPSS software package. However, modifications have been made and all examples have been/will be re-worked using both R and SAS. I hope that in the future I'll also add Stata, though I no longer have access to it; I hope to have it again in the fall of 2013.

Some Useful Links

A link to some old statistics resources I once posted; I no longer have access to this page and cannot verify that all links work or change broken ones any more.

SPSS's web page

SPSS trial version for download

David Howell's

*Statistical Methods*WebpageAndy Fields'

*Discovering Statistics*(aka www.statisticshell.com) WebpageFor the fourth edition of the text, SAGE Publications put up a site here.

R, a commonly used, free statistical software package/language

SAS, a commonly used statistical software package (alas, not free)

Stata, a commonly used statistical software package (alas, not free)

**NEW:**In my examples of R below, I always use syntax. However, some people don't like syntax. It's possible to make R behave like SPSS. If you JUST can't be bothered by syntax, here's how to make R pretty much just like SPSS (this even includes how to work with an SPSS data set in R when you*don't have*SPSS but just have an SPSS file). A link to a document by John Fox entitled "Getting Started with the R Commander" is also useful.

Week 1

Data used in class (SPSS)

SPSS Syntax used example (accesses Data above) for Day 1 lecture

My video on SPSS to correspond with Day 1 lecture

Wilkinson Article (pdf)

A handout on reporting statstics.

Howell's Bad Cancer.dat in SPSS Format

Howell's Table 2-1 in SPSS Format

*StÎ±tz*4 Life Video

R Syntax for self-contained example for Day 1 lecture

SAS Syntax for self-contained example for Day 1 lecture

Week 2

Kelley & Preacher (2012). On effect size. (pdf)

Cohen (1992). A power primer. (pdf)

Paperclip Example Data from Class (no syntax, all we did was means and standard deviations, which you know how to do)

Height/Weight Data from Class

SPSS Syntax for Height/Weight Example from Class

Howell's Data for Figure 2.1/Table 2.2 in SPSS Format

Week 3

t-test syntax (SPSS)

t-test data (SPSS)

Our example on t-tests

An amusing video on power

Homework #3 Data

R syntax for self-contained example of t-tests

R syntax that accesses SPSS data set and then runs t-test examples

SAS syntax for self-contained example of t-tests (coming soon)

SAS syntax that accesses SPSS data set and then runs t-test examples (coming soon)

Week 4

Week 5

Multiple Comparison Procedure Data

Multiple Comparison Procedure Syntax (includes LMATRIX for orthogonal contrasts)

Toothacher's book on multiple comparison procedures

UCLA's webpage on the planned comparisons portion of Geoff Keppel's ANOVA course (MANOVA was not covered in class, but GLM was)

Homework #5 Data

R Syntax

SAS Syntax

Week 6

Factorial ANOVA Data

Factorial ANOVA Syntax (includes simple main effects/simple effects syntax)

Equations for the factorial ANOVA

Homework #6 Data

R Syntax

SAS Syntax

Week 7

Repeated Measures/Mixed ANOVA Data

Repeated Measures/Mixed ANOVA Syntax

Take Home Portion of Midterm Exam

Data for Take Home Portion of Midterm Exam

Homework #7 (Due After Midterm, on week 9)

R Syntax

SAS Syntax

SPSS Syntax to perform repeated measures ANOVA as a mixed effects model (includes flipping syntax) -- not covered in class, but Howell discusses

Week 8

Midterm Exam - In Class

Week 9

Licht (2004) Chapter (pdf)

Correlation and Simple Regression Data

Correlation and Simple Regression Syntax

A web page about extrapolation in regression

Some Halloween humor

R Syntax

SAS Syntax

Week 10

Multiple Regression Data

Multiple Regression Syntax

Some notes on regression and correlation

An example of an APA style regression table

A piece on cautions related to using stepwise regression

Bem (2011) article mentioned in class on psi phenomenon/ESP

French's (2012) post about trying to publish replications

Ioannidis (2004) article on published findings being wrong

Homework #8 Data

R Syntax

SAS Syntax

Week 11

Moderation Example Handout

Cohen, Cohen, West, and Aiken data for moderation/simple slopes example

Cohen, Cohen, West, and Aiken syntax to run moderation and simple slopes analysis

Baron & Kenny (1986) Article (pdf)

Holmbeck (2002) Article (pdf)

Homework #9 Data

Week 12

THANKSGIVING - No Class

Week 13

Mediation Example Handout

Mediation Example Data

Mediation Example Syntax

A mediation power point slide show

The In-N-Out Burger website

Chi-Squared and Logistic Regression Handout (we didn't cover logistic regression -- see EXTRAS)

Chi-Squared and Logistic Regression Data to accompany handout

Chi-Squared Syntax

Article to accompany Week #10 Homework (the source of your homework)

Article on why it's a bad idea to turn a continuous variable into a categorical one

Homework #10 Data

R Syntax

SAS Syntax

EXTRAS

Because we didn't get to Logistic Regression in class, I have this great chapter

Here's data from the Titanic on who lives or dies. This data is more complete than that used in the chapter, so the numbers won't match the chapter exactly. However, the variables are the same and you can try the models in the chapter for fun!

Week 14

ANCOVA Handout

ANCOVA Data

ANCOVA Syntax

General Linear Models Lecture (coming soon)

Cohen (1968) General Linear Model Article (pdf)

Exam Review - Bring your questions to ask (I won't post what you ask here, but that's part of today's plan)

Key to Homework #10 (you won't get it back before the exam)

Final Exam Take Home

Final Exam Take Home Data

R Syntax

SAS Syntax

Week 15

Final Exam In Class