
IBM SPSS Statistics 19 Advanced Statistical Procedures Companion
Pearson (Publisher)
Published on 28. July 2011
Book
Mixed media product
464 pages
978-0-321-74843-0 (ISBN)
Description
IBM SPSS Statistics 19 Advanced Statistical Procedures Companion contains valuable tips, warnings, and examples that will help you take advantage of IBM SPSS Statistics to better analyze data. This book offers clear and concise explanations and examples of advanced statistical procedures in the IBM SPSS Statistics Advanced and Regression modules.
More details
Language
English
Place of publication
United States
Publishing group
Pearson Education (US)
Target group
College/higher education
Dimensions
Height: 190 mm
Width: 233 mm
Thickness: 16 mm
Weight
644 gr
ISBN-13
978-0-321-74843-0 (9780321748430)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Other editions
Previous edition
Marija J. Norusis | Inc. SPSS Inc.
PASW Statistics 18 Advanced Statistical Procedures
Book
03/2010
Pearson
€49.51
Article exhausted; check for reprint
Persons
Marija Norusis earned a PhD in biostatistics from the University of Michigan. She was SPSS's first professional statistician. During this time, she wrote her first book, The SPSS Introductory Guide. Since then she has written numerous volumes of highly acclaimed SPSS documentation, and textbooks that demystify statistics and SPSS. Dr. Norusis has been on the faculties of the University of Chicago and Rush Medical College, teaching statistics to diverse audiences. When not working on SPSS guides, Marija analyzes real data as a statistical consultant.
For more detailed information about Dr. Norusis and her SPSS guides, visit her website at www.norusis.com.
For more detailed information about Dr. Norusis and her SPSS guides, visit her website at www.norusis.com.
Content
1. Model Selection Loglinear Analysis
2. Logit Loglinear Analysis
3. Multinomial Logistic Regression
4. Ordinal Regression
5. Probit Regression
6. Kaplan-Meier Survival Analysis
7. Life Tables
8. Cox Regression
9. Variance Components
10. Linear Mixed Models
11. Generalized Linear Models
12. Generalized Estimating Equations
13. Generalized Linear Mixed Models
14. Nonlinear Regression
15. Two-Stage Least-Squares Regression
16. Weighted Least-Squares Regression
17. Multidimensional Scaling
2. Logit Loglinear Analysis
3. Multinomial Logistic Regression
4. Ordinal Regression
5. Probit Regression
6. Kaplan-Meier Survival Analysis
7. Life Tables
8. Cox Regression
9. Variance Components
10. Linear Mixed Models
11. Generalized Linear Models
12. Generalized Estimating Equations
13. Generalized Linear Mixed Models
14. Nonlinear Regression
15. Two-Stage Least-Squares Regression
16. Weighted Least-Squares Regression
17. Multidimensional Scaling