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E-raamat: IBM SPSS by Example: A Practical Guide to Statistical Data Analysis

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  • Formaat: PDF+DRM
  • Ilmumisaeg: 31-Dec-2014
  • Kirjastus: SAGE Publications Inc
  • Keel: eng
  • ISBN-13: 9781483319063
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IBM SPSS by Example: A Practical Guide to Statistical Data AnalysisSuurem pilt
  • Formaat: PDF+DRM
  • Ilmumisaeg: 31-Dec-2014
  • Kirjastus: SAGE Publications Inc
  • Keel: eng
  • ISBN-13: 9781483319063
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A practical, accessible guide for using SPSS in doing data analysis. Designed to work across disciplines, the authors have provided a number of SPSS ”step-by-step" examples in most chapters showing the user how to plan a study, prepare data for analysis , perform the analysis and interpret the output from SPSS. In addition, the authors provide helpful hints and insights through the features "Tips and Caveats" and "Sidebar".

The 2nd edition includes two new chapters -- "Creating and Using Graphs" and "Factor Analysis". In addition, a new section on Syntax has been included in an appendix. All chapters have been updated to reflect current menu options along with many SPSS screenshots making the process much simpler for the user.



Containing numerous step-by-step examples throughout, this new edition introduces readers to how to use IBM SPSS to plan a study, prepare data for analysis, perform the analysis and interpret the output.

Arvustused

"This text not only helps the user to quickly navigate SPSS, but also provides critical aspects of each of the tests I do not think that there is a better text for SPSS users who are looking for a quick introduction and succinct guidance." -- Philip J. Murphy, Monterey Institute of International Studies "All in all, [ this text] will become an indispensable tool for anyone that seeks to use statistical procedures to analyze data and to report the same effectively." -- Tyrone Bynoe, University of the Cumberlands "[ This text is] very readable and comprehensible for intermediate level students." -- Alan Davis, University of Colorado Denver

List of Tables and Figures xi
Preface & Acknowledgments xxi
About the Authors xxiii
1 Introduction 1(20)
Getting the Most Out of IBM SPSS by Example
2(1)
A Brief Overview of the Statistical Process
3(2)
Understanding Hypothesis Testing, Power, and Sample Size
5(4)
Understanding the p-Value
9(1)
Planning a Successful Analysis
10(2)
Guidelines for Creating Data Sets
12(5)
Preparing Excel Data for Import
17(1)
Guidelines for Reporting Results
18(1)
Downloading Sample SPSS Data Files
19(1)
Opening Data Files for Examples
19(2)
2 Describing and Examining Data 21(28)
Example Data Files
22(1)
Describing Quantitative Data
22(13)
Describing Categorical Data
35(14)
3 Creating and Using Graphs 49(26)
Introduction to SPSS Graphs
49(1)
Guidelines for Creating and Using Graphs
49(1)
Chart Builder
50(1)
Graphboard Template Chooser
51(1)
Legacy Plots
51(1)
Scatterplots
52(10)
Histograms
62(4)
Bar Charts
66(4)
Pie Charts
70(2)
Boxplots
72(3)
4 Comparing One or Two Means Using the t-Test 75(34)
One-Sample t-Test
75(7)
Two-Sample t-Test
82(18)
Paired t-Test
100(9)
5 Correlation and Regression 109(36)
Correlation Analysis
109(10)
Simple Linear Regression
119(10)
Multiple Linear Regression
129(16)
6 Analysis of Categorical Data 145(40)
Contingency Table Analysis (r x c)
146(18)
McNemar's Test
164(4)
Mantel-Haenszel Comparison
168(5)
Tests of Interrater Reliability
173(4)
Goodness-of-Fit Test
177(5)
Other Measures of Association for Categorical Data
182(3)
7 Analysis of Variance and Covariance 185(46)
One-Way ANOVA
185(18)
Two-Way Analysis of Variance
203(9)
Repeated-Measures Analysis of Variance
212(9)
Analysis of Covariance
221(10)
8 Nonparametric Analysis Procedures 231(22)
Spearman's Rho
232(4)
Mann-Whitney-Wilcoxon (Two Independent Groups Test)
236(3)
Kruskal-Wallis Test
239(4)
Sign Test and Wilcoxon Signed-Rank Test for Matched Pairs
243(5)
Friedman's Test
248(5)
9 Logistic Regression 253(18)
Introduction to Logistic Regression
253(1)
Simple Logistic Regression
254(6)
Multiple Logistic Regression
260(11)
10 Factor Analysis 271(24)
Appropriate Applications for a Factor Analysis
272(1)
Design Considerations for Factor Analysis
273(1)
Hypotheses for Factor Analysis
274(1)
Factor Analysis/Dimension Reduction
274(21)
Appendix A. A Brief Tutorial For Using IBM SPSS For Windows 295(26)
Appendix B: Choosing The Right Procedure To Use 321(4)
Index 325
Alan Elliott is the Director of the Statistical Consulting Center at Southern Methodist University within the Department of Statistical Science. Previously he served as a statistical consultant in the Department of Clinical Science at the University of Texas Southwestern Medical Center at Dallas for 30 years. Elliott holds masters degrees in Business Administration (MBA) and Applied Statistics (MAS). He has authored or coauthored over 35 scientific articles and over a dozen books including the Directory of Microcomputer Statistical Software, Microcomputing with Applications, Using Norton Utilities, SAS Essentials, Applied Time Series Analysis, and Statistical Analysis Quick reference Guidebook with SPSS Examples. Elliott has taught university-level courses in statistics, statistical consulting, and statistical computing for over twenty-five years. 

Wayne A. Woodward, Ph.D., is a Professor of Statistics and chair of the Department of Statistical Science at Southern Methodist University. He is a fellow of the American Statistical Association and was the 2004 recipient of the Don Owen award for excellence in research, statistical consulting, and service to the statistical community. In 2007 he received the Outstanding Presentation Award given by the Section on Physical and Engineering Sciences at the 2007 Joint Statistical Meetings in Salt Lake City, Utah. In 2003 he was named a Southern Methodist University Distinguished Teaching Professor by the universitys Center for Teaching Excellence, and he received the 2006-2007 Scholar/Teacher of the Year Award at SMU, an award given by the United Methodist Church. . Over the last 35 years he has served as statistical consultant to a wide variety of clients in the scientific community and has taught statistics courses ranging from introductory undergraduate statistics courses to graduate courses within the Ph.D. program in Statistics at Southern Methodist University. He has been funded on numerous research grants and contracts from government and industry to study such issues as global warming and nuclear monitoring.  He has authored or coauthored over 70 scientific papers and four books. 
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