Michael Chajewski's Teaching Materials

Structural Equation Modeling (SEM)
Lab for course taught by Dr. Ming-mei Wang

Lab 1: Introduction to SEM
Powerpoint slides introducing basic SEM concepts.
Data: Assessment data (227)
Data from classroom assessments (with 227 cases).
Lab 2: Data screening & regression
Topics covering screening your data in LISREL and reviewing simple linear regression.
Data: LISREL data (162)
Data from classroom assessments (with 162 cases).
Lab 3: Multiple regression
Topics covered regarding multiple regression.
Lab 3: Multiple regression example
Worked out example of multiple regression in LISREL.
Lab 4: Path analysis
Topics covered regarding path analysis.
Lab 4: Path analysis example
Worked out example of a simple path analysis in LISREL.
Lab 5: Modification indices I
Topics covered regarding using modification indices.
Lab 5: Modification indices example I
Worked out example of interpreting indices and introduction to goodness of fit.
Lab 6: Modification indices II
More topics regarding using modification indices.
Lab 6: Modification indices example II
Example of using the indices to build better fitting models.
Lab 7: Modification indices III
Topics regarding modification indices and their extended use.
Lab 7: Modification indices example III
Example of using the indices to make better fitting models by trimming.
Data: Illness factor data
Data from Rex B. Kline (2005) Table 6.1 on page 124.

Multivariate Data Analysis
Lab for course taught by Dr. David Budescu

Lab 1: Introduction to SAS
SAS syntax for manipulating data and reading in files.
Data: An Excel file
Data: A Dat file
Data: An SPSS file
Data: An SPSS portable file
Data: A Txt file
Data: A CSV file
Lab 2: Matrix operations
Basic matrix operations in SAS using proc iml.
Hmw 1: Matrix operations
First homework assignment using matrix operations to solve as system of linear equations.
Hmw 1: Answer key
Hmw 1: SAS syntax
Lab 3: Outliers
Detecting univariate and multivariate outliers.
Data: Chapter 3 data
Raykov and Marcoulides (2008) chapter 3 sample data.
Lab 4: Multivariate normality
Assessing multivariate normality.
Data: Crime data
Composit crime SAS dataset for all 50 states.
Lab 4: SAS multnorm macro
SAS macro to produce Mardia's coefficients.
Hmw 2: Multivariate normality
Second homework assignment evaluating multivariate normality.
Hmw 2: Answer key
Hmw 2: SAS syntax
Hmw 2: Data
Lab 5: One-sample Hotelling's T-squared
Testing for multivariate mean vector differences.
Lab 6: Two-samples Hotelling's T-squared
Testing for multivariate mean vector differences in two independent samples.
Data: Swiss bank note data
Excel file of Swiss bank note data.
Hmw 3: Two independent samples
Checking multivariate normality and comparing two samples.
Hmw 3: Answer key
Hmw 3: SAS syntax
Hmw 3: Data
Lab 7: One-way MANOVA
Demonstrating a one-way multivariate analysis of variance.
Data: Pottery data
Excel file of pottery shards recovered at different sites.
Lab 7: SAS multnormplt macro
SAS macro to produce Mardia's coefficients and additional tests.
Lab 7: Proc iml graph
SAS proc iml routine producing a scatter plot matrix with confidence ellipses.
Hmw 4: One-way MANOVA
Using SAS to test for a one-way MANOVA in crude oil samples.
Hmw 4: Answer key
Hmw 4: SAS syntax
Hmw 4: Data
Hmw 4: Lambda Verification
An Excel spreadsheet verifying Wilk's Lambda computations
Lab 8: One-way MANOVA II
Continuing demonstration of one-way multivariate analysis of variance.
Lab 9: Factorial MANOVA
Demonstrating a multi-way multivariate analysis of variance.
Data: Social desirability data
SAS data file of counseled people at community center with risk of psychopathology.
Hmw 5: Factorial MANOVA
Using SAS to test a multi-way MANOVA in an assessment battery for troubled youth.
Hmw 5: Answer key
Hmw 5: SAS syntax
Hmw 5: Data
Lab 10: Repeated Measures
Demonstarting the Repeated Measures ANOVA and MANOVA procedures.
Data: High school students' stress scores
Data file of stress scores for high school students in their freshmen, sophomore, junior and senior years.
Hmw 6: Repeated Measures
Hmw 6: Answer key
Lab 11: Principal Components
Replicating the Raykov and Marcoulides Chapter 7 PCA example
Data: Chapter 7 exercise 1 data
Lab 12: Exploratory Factor Analysis
Extending PCA to EFA.
Data: Exploring the latent structure of different geographic places
Hmw 7: EFA
Hmw 7: Answer key
Hmw 7: SAS syntax
Hmw 7: Data
Olympic runners' track records by countries.
Lab 13: Canonical Correlation
Canonical correlation using two SAS procs.
Data: Bank employee evaluation data
Hmw 8: Canonical Correlation
Hmw 8: Answer key
Hmw 8: SAS syntax
Hmw 8: Data
Marsh soil and water samples measuring chemical concentration.
Lab 14: Discriminant Function Analysis I
An introduction to DFA.
Data: Psychological job data
Variables believed to predict job position membership.
Hmw 9: Link
DFA example from the statistics department of the Unievrsity of Pennsylvania.
Lab 15: Discriminant Function Analysis II
An elaboration of DFA with alternate methods, applications and resproductions of estimates.

Regression
Lab for course taught by Dr. Se-Kang Kim

Computer Repair Data
Lab data on computer unit repair.
Dr. Kim's Data
Data used in Dr. Kim's notes.
Chatterjee p.10 Data
Data from the Chatterjee and Hadi (2006) book page 10.
Chatterjee p.122 Data
Data from the Chatterjee and Hadi (2006) book page 122.
Chatterjee p.132 Data
Data from the Chatterjee and Hadi (2006) book page 132.
Chatterjee p.172 Data
Data from the Chatterjee and Hadi (2006) book page 172.
Chatterjee p.224 Data
Data from the Chatterjee and Hadi (2006) book page 224.
Multicollinearity using PCA
An explanation of SPSS procedures computing kappa (a multicollinearity measure) using Principal Components Analysis (PCA).
ANCOVA example
A computational example of Analysis of Covariance (ANCOVA) by regression.

Introductory Psychology
Lab for course taught by Dr. Joshua Brown

Fall 2007 Syllabus
Lab syllabus for the fall academic semester 2007.
Spring 2008 Syllabus
Lab syllabus for the spring academic semester 2008.
Lab One
First lab packet. Library research and PsychINFO review.
APA Crib Sheet
Essentials of APA style required in academic/professional writing.
Lab Two
Second lab packet. The Monty Hall Problem: A demonstration in probability.
Lab Three
Neuropsychology lab. Taking a closer look at brain dexterity.
LHBB Answer Sheet
Corrected brain dexterity record sheet with computational formulas.
Operant Conditioning Lab
This is the 'Rat Lab' to be conducted in the animal lab.
Rat Observation Sheet
Answer sheet for behavioral latencies and rat behavior.
Sniffy
Virtual rat lab alternative.
Lab Five
The Mueller-Lyer Illusion.
Lab Six
Serial learning and memory.
Lab Six Class Data
Composit SPSS data for serial learning lab.
Cellphone Lab
Analyzes the differences in groups in their time spent on the phone.
Sample Cellphone Data
Simulated SPSS responses for the Cellphone Lab.
Sleep Lab
Analyzes the pattern of sleep for seven nights.
Sample Sleep Lab Data
Simulated SPSS responses for the Sleeb Lab.

Introductory Statistics
Lab for course taught by Dr. Se-Kang Kim

Summer 2008 Syllabus
Lab syllabus for the summer academic semester 2008.
Volunteer Narrative
Hospital compilation of volunteer data.
Volunteer Data
Transcribed and entered volunteer data.
Answers #1
True/Flase and Multiple Choice homework answers (Lab 1-4).
Answers #2
True/Flase and Multiple Choice homework answers (Lab 5-7).

Teaching