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Spss 14.0 Statistical Procedures Companion - Softcover

 
9780131995277: Spss 14.0 Statistical Procedures Companion

Synopsis

The SPSS 14.0 Statistical Procedures Companion covers many of the more advanced statistical procedures in SPSS, which are not discussed in the SPSS 14.0 Guide to Data Analysis.  This book is intended as the continuation of the GDA.  The audience is no longer the beginning student but is instead the data analyst, either an advanced student or a professional. The Companion offers practical suggestions and emphasizes topics that arise when analyzing real data for presentations, reports, and dissertations, instead of the pristine data of homework assignments.  A data CD is included with this book.

 

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.

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From the Back Cover

Data CD-ROM included.

The SPSS® 11.0 Guide to Data Analysis is a friendly introduction to both data analysis and SPSS, the world's leading desktop statistical software package. Easy-to-understand explanations and in-depth content make this guide both an excellent supplement to other statistics texts and a superb primary text for any introductory data analysis course. With the SPSS® 11.0 Guide to Data Analysis, you get a jump-start on describing data, testing hypotheses, and examining relationships using SPSS.

For SPSS 11.0, author Marija Norusis incorporates a wealth of new data, including the General Social Survey for 2000 and studies of Internet usage, opinions of the criminal justice system, marathon running times, library patronage, and the importance of manners. These new data files are supplied with the book and are used throughout the examples and expanded chapter exercises. This unique combination of examples, exercises, and contemporary data gives you hands-on experience in analyzing data and makes learning about data analysis and statistical software relevant, unintimidating, and even fun!

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Advanced Statistical Procedures Companion 13.0

Preface

With judicious doses of common sense, well-constructed graphs, and simple statistical analyses, you can answer many interesting and important questions. That should always be your goal. However, some questions require more sophisticated statistical analyses. A statistical procedure is not like a sausage; you want to know its contents. You want to know the types of questions and data appropriate to a particular procedure. You also want to know how to interpret the output that it produces. The goal of the SPSS 13.0 Advanced Statistical Procedures Companion is to provide you with background information and examples for statistical procedures contained in the SPSS Advanced and Regression 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 your mute data file.

A closely related book, the SPSS 13.0 Statistical Procedures Companion(Norusis, 2005) focuses on the most frequently used procedures in the SPSS Base system, as well as the widely used logistic regression procedure from the Regression Models option and log linear models from the Advanced Statistics option. It also contains introductory chapters on using the software, creating and cleaning data files, testing hypotheses, and describing data. Numerous tips and warnings for analyzing data and using SPSS are incorporated. For an introduction to statistical concepts and the fundamentals of data analysis, see the SPSS 13.0 Guide to Data Analysis (Norusis, 2005).

About This Book

Each of the chapters uses one or more data files, most of which can be found on the accompanying CD. Step-by-step instructions are included for obtaining the analyses described in the book. All of the statistical algorithms for the procedures can be accessed from the SPSS Web site, www.spss.com. Select Support and then Login to Support. If you do not have a User ID and password, you can use Guest for both. Next, select Statistics and then Algorithms. If you are reading the preface online without access to the table of contents, here's what the book contains:

  • 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
  • Ordinal regression models to examine predictors of ratings of the justice system
  • 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 analysisto 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

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