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Quant Methods 3                                                                                 

Note: <Print> indicates printable files. <Visit> indicates the web site you can visit. <Save> indicates files to be saved. <More> indicates optional materials (advanced).

(VH) stands for Video Handout (the hand out that goes with videos).

1. Introduction - Syllabus, Outline, Atlanta Schools,

2.  Simple Regression

<Print>  Notes (VH), Exercise 1 - Simple Regression,

<Visit> Princeton University - Intro to Regression, UCLA Academic Technology Services (SPSS Web Books - Chapter 1. Simple and Multiple Regression), UCLA Academic Technology Services (SPSS Web Books - Chapter 2. Regression Diagnostics), www.weibull.com (Simple Linear Regression Analysis),

<Save> Variance.xlsx, srSPSS.sav

<More> Finding Least Squares Estimators for Simple Linear Regression (Neel, 1991), Four Assumptions Of Multiple Regression That Researchers Should Always Test,    Duke University (Testing the assumptions of linear regression) Checking assumptions in regression (SAS), Indiana University (Univariate Analysis and Normality Test Using SAS, Stata, and SPSS), Multiple Regression Assumptions. ERIC Digest.

3.  Multiple Regression 

<Print> Notes (VH)

<Visit>Virginia Tech (Multiple Regression), Hierchical Multiple Regression (Part 1 - Part 4)

<Save> multiple.sav, regression plane.xlsx, ExcelRegression.xls

<More> missouristate.edu (Multiple Regression with Two Predictor Variables), ExcelRegression.mp4

4.  Matrix Operations

<Print> Notes (VH)

<More> Univ. of Colorado (Intro to Matrix Algebra) PDF,

5.  Partial and Semipartial Correlation

<Print> Notes (VH), Exercise 2 - Correlation Analysis,

<More> Sevens (2003) Partial and Semipartial Correlation PDF

6.  Regression Diagnostics

<Print> Notes (VH) 

<Save> SPSS *.sav (Y.SAV, YA.SAV, YB.SAV,YC.SAV)

<More> UCLA Academic Technology Services Statistical Computer Seminars (Regression Using SPSS) - Great Videos,

 

     How Many Subjects

<Print> Notes (ppt) (VH), Notes (Green's), GPower3-BRM-Paper, GPower31-BRM-Paper

<Visit> G*Power Web site

7.  Riview - Sample Practice Questions,

8.  Exam

9.  Prediction

<Print> Notes (VH)

<Save> studyhour.sav, pred.xlsx

<More> Prediction in Multiple Regression (PARE article), Onlinestatbook Chapter 12, Applet to do a quick regression calculation

10. Model Validation  

<Print> Notes (VH),   Stevens' Textbook pp.113-119 ,

<Save> Adjusted R-square Excel program,     

<More> Note on Shrinkage, Crueton 1951 (p. 692), Lord and Novick 1968 (pp. pp. 284 293), Raju et al. 1999, Algina and Keselman (2000)

11. Model Selection

<Print> Notes1 Notes2, Huberty's article,

<Visit> The problem of too many variables, East Carolina University,

<Save> model.sav,  all_possible_mydata.SPS,  all_possible_regressions.xlsx   

<More>  Introduction to Multiple Regression: How Much Is Your Car Worth?,  How Much is Your Car Worth (pdf),   JSE Car Lab Final.xls,                     

12. t-test and ANOVA

<Print> t test Notes (VH), ANOVA Notes 1 (VH), ANOVA Notes 2 (VH), Mind Your Quants and Quals,

<Save> dummyttest.sav, dummycoding_z.SPS, dummyanova.sav, carlab.sav, dummycoding_car.SPS

13. ANCOVA

<Print> ANCOVA Review (VH),  Notes (VH),  Johnson-Neyman Procedure - Notes (VH),

<Visit>

<Save> ANCOVA_REGRESSION.sav , QJN.xlsx, JN_GPA_SPSS_SYNTAX.sps

 

14. More Topics

<Print>  Notes on More Topics (VH)

<More> HLM and SEMAge Study,  Corey's Advanced Statistical Methods “One-Pagers”                                                                     

15. Review