Using SPSS for Windows

Data Analysis and Graphics
2. 2005 Auflage 2005
ISBN: 978-0-387-40083-9
Verlag: Springer

Buch, Englisch, 228 Seiten, Format (B × H): 177 mm x 234 mm, Gewicht: 472 g

This book is a self-teaching guide to the SPSS for Windows computer application. It is designed to be used with SPSS version 13.0, although many of the procedures are also applicable to earlier versions of SPSS. The step-by-step format of this manual “walks” the reader through numerous examples, illustrating how to use the application. The results produced in SPSS are shown and discussed in most examples. Each chapter demonstrates statistical procedures and provides exercises to reinforce the text examples. This book may be used in two ways – as a stand-alone manual for a student learning to use SPSS for Windows or in a course together with a basic statistics text. As a stand-alone manual, it is assumed that the reader is familiar with the basic ideas of quantitative data and statistical analysis. Thus, statistical terminology is used without providing extensive definitions. Most of the applications in this book are self-explanatory, although the reader will need to refer to a text for extensive discussion of statistical theory and procedures.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Gerber, Susan B

Finn, Kristin Voelkl

Fachgebiete

• Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsmathematik und -statistik
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Datenanalyse, Datenverarbeitung
• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
• Mathematik | Informatik EDV | Informatik Business Application Mathematische & Statistische Software
• Wirtschaftswissenschaften Volkswirtschaftslehre Volkswirtschaftslehre Allgemein Ökonometrie

Inhaltsverzeichnis

The Nature of SPSS.- Summarizing Data Graphically.- Summarizing Data Numerically: Measures of Central Tendency.- Summarizing Data Numerically: Measures of Variability.- Summarizing Multivariate Data: Association Between Numerical Variables.- Summarizing Multivariate Data: Association Between Categorical Variables.- Basic Ideas of Probability.- Probability Distributions.- Sampling Distributions.- Answering Questions About Population Characteristics.- Differences Between Two Populations.- Inference on Categorical Data.- Regression Analysis: Inference on Two or More Numerical Variables.- ANOVA: Comparisons of Several Populations.- Exploratory Factor Analysis.