Description
Springer Using Spss For Windows 2Ed Data Analysis And Graphics by Susan B. Gerber , Kristin Voelkl Finn
The second edition of this popular guide demonstrates the process of entering and analyzing data using the latest version of SPSS (12.0), and is also appropriate for those using earlier versions of SPSS. The book is easy to follow because all procedures are outlined in a step-by-step format designed for the novice user. Students are introduced to the rationale of statistical tests and detailed explanations of results are given through clearly annotated examples of SPSS output. Topics covered range from descriptive statistics through multiple regression analysis. In addition, this guide includes topics not typically covered in other books such as probability theory, interaction effects in analysis of variance, factor analysis, and scale reliability. Chapter exercises reinforce the text examples and may be performed for further practice, for homework assignments, or in computer laboratory sessions.This book can be used in two ways: as a stand-alone manual for students wishing to learn data analysis techniques using SPSS for Windows, or in research and statistics courses to be used with a basic statistics text. The book provides hands-on experience with actual data sets, helps students choose appropriate statistical tests, illustrates the meaning of results, and provides exercises to be completed for further practice or as homework assignments.Susan B. Gerber, Ph.D. is Research Assistant Professor of Education at State University of New York at Buffalo. She is director of the Educational Technology program and holds degrees in Statistics and Educational Psychology.Kristin Voelkl Finn, Ph.D. is Assistant Professor of Education at Canisius College. She teaches graduate courses in research methodology and conducts research on adolescent problem behavior. 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.