PASW Statistics 18 Advanced Statistical Procedures
Pearson (Publisher)
Published on 5. March 2010
Book
Paperback/Softback
432 pages
978-0-321-69057-9 (ISBN)
Article exhausted; check for reprint
Description
PASW Statistics 18 Advanced Statistical Procedures contains valuable tips, warnings, and examples that will help you take advantage of PASW (formerly SPSS) to better analyze data. This book offers clear and concise explanations and examples of advanced statistical procedures in the PASW 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: 235 mm
Width: 191 mm
Weight
592 gr
ISBN-13
978-0-321-69057-9 (9780321690579)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Other editions
New editions

Marija Norusis | Inc. SPSS
IBM SPSS Statistics 19 Advanced Statistical Procedures Companion
Book
07/2011
Pearson
€50.97
Article is exhausted; no reprint
Previous edition

Marija Norusis
SPSS 17.0 Advanced Statistical Procedures Companion
Book
04/2009
Pearson
€39.60
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. Nonlinear Regression
14. Two-Stage Least-Squares Regression
15. Weighted Least-Squares Regression
16. 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. Nonlinear Regression
14. Two-Stage Least-Squares Regression
15. Weighted Least-Squares Regression
16. Multidimensional Scaling