Statistics

A statistical procedure is not like a sausage: you want to know its contents; you want to know the types of questions it can be used to answer and the types of data for which it is appropriate. The goal of the SPSS 15.0 Advanced Statistical Procedures Companion is to provide you with background information and examples for statistical procedures in the SPSS Advanced and Regression Models modules. It aims to make it less likely that you will succumb to the siren song of melodic statistical procedure names and unleash a disastrous assault on a mutely suffering data file.

For additional information, go to http://www.norusis.com.  This site offers a detailed Table of Contents, features, examples included in the book, and a sample chapter for download.

If you want clear and concise explanations and examples of the statistical procedures in the SPSS Advanced and Regression modules, this book is for you.

You'll use:

·         Nonlinear regression to model population growth

·         Logit loglinear models to study voting behavior

·         Multinomial regression to predict degree of support for spending money on space exploration

·         Loglinear model selection to identify models that describe the relationships between happiness, marital status, and income

·         Life table analysis to estimate the longevity of employees at a company

·         Kaplan-Meier analysis to look at the distribution of survival times after diagnosis of a disease

·         Cox proportional hazards models to evaluate the impact of age, histology, and stage of the disease on survival

·         Variance components analysis to estimate components of variability

·         Linear mixed models to study achievement scores when observations are correlated

·         Weighted least-squares analysis to accommodate observations with unequal variability in a regression model

·         Two-stage least-squares analysis to allow correlations between predictor variables and errors

·         Probit regression models to estimate the relationship between dosages of a drug and the response rate

·         Multidimensional scaling (ALSCAL) to construct objective scales of subjective attributes

·         Generalized linear models to extend the General Linear Model to situations in which the dependent variable is not normally distributed and/or the relationship between the dependent variable and the independent variables is linear by way of a link function.

·         Generalized estimating equations to extend the General Linear Model to accommodate correlated data.

A CD containing many of the data sets used in this book is included.

See the SPSS 15.0 Statistical Procedures Companion for a friendly, unintimidating introduction to using SPSS for analyzing data. You'll learn how to describe data, test hypotheses, and build models. You'll analyze real data sets using regression analysis, factor analysis, discriminant analysis, logistic regression, ordinal regression, cluster analysis, reliability, loglinear models, and general linear models.

Contents at a glance:

Models for categorical dependent variables:
Multinomial regression models
Ordinal regression models (PLUM)
Logit and probit models
Hierarchical loglinear models

Models for time-to-event (survival) data:
Actuarial life tables
Kaplan-Meier estimates
Cox regression, with and without time-dependent covariates

Regression models:
Nonlinear regression
Two-stage least squares
Weighted least squares

Additional procedures:
Linear mixed models
ALSCAL
Variance-component estimation

SPSS Procedural Manuals & Guides (Statistics)

SPSS^® 16.0: Advanced Statistical Procedures Companion contains valuable tips, warnings, and examples that will help you take advantage of SPSS and better analyze data. This book offers clear and concise explanations and examples of advanced statistical procedures in the SPSS Advanced and Regression modules.

• SPSS 16.0 Advanced Statistical Procedures Companion
  Norusis
  © 2009 | Prentice Hall | Paper; 432 pages | Instock
  ISBN-10: 0136061400 | ISBN-13: 9780136061403
  Brief Description | Buy from myPearsonStore
  

<>Marija Norušis earned a Ph.D. in biostatistics from the University of Michigan. She was SPSS's first professional statistician. McGraw-Hill published 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. Norušis 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 those whose Lithuanian is rusty:
"Marija" is pronounced "Maria," not "Mar-eye-ja."
"Norušis" is pronounced "Norooshis," not "Neurosis."

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Pearson Higher Education offers special pricing when you choose to package your text with other student resources. If you're interested in creating a cost-saving package for your students contact your Pearson Higher Education representative.