SPSS 8.0 guide to data analysis
著者
書誌事項
SPSS 8.0 guide to data analysis
Prentice Hall, 1998
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注記
Includes "Data disk to accompany SPSS 8.0 Guide to data analysis."
Bibliography: p. 553
Includes index
System requirements for accompanying computer disk: Windows 95 or Windows NT 4.0
内容説明・目次
内容説明
For undergraduate or graduate courses in which greater knowledge of SPSS as a tool for data analysis is desired. Also for courses in Data Analysis.
This text introduces the concepts of data analysis from collecting and coding data to interpreting the results of statistical analyses. The emphasis is on understanding fundamental concepts such as data distributions and different kinds of relationships. Simulations and analyses of real data are used to illustrate statistical concepts and models. Chapter summaries and exercises reinforce learning. In addition to teaching statistics, this guide includes instructions for operating the full or student version of SPSS 8.0 for Windows. Extensive problem sets using the companion data disk make this both a useful textbook and reference tool.
目次
1. GETTING STARTED WITH SPSS.
1. Introduction.
2. An Introductory Tour: SPSS for Windows.
2. DESCRIBING DATA.
3. Counting Responses.
4. Computing Descriptive Statistics.
5. Comparing Groups.
6. Looking at Distributions.
7. Counting Responses for Combinations of Variables.
8. Plotting Data.
3. TESTING HYPOTHESES.
9. Evaluating Results from Samples.
10. The Normal Distribution.
11. Testing a Hypothesis about a Single Mean.
12. Testing a Hypothesis about Two Related Means.
13. Testing a Hypothesis about Two Independent Means.
14. One-Way Analysis of Variance.
15. Two-Way Analysis of Variance.
16. Comparing Observed and Expected Counts.
17. Nonparametric Tests.
4. EXAMINING RELATIONSHIPS.
18. Measuring Association.
19. Linear Regression and Correlation.
20. Testing Regression Hypotheses.
21. Analyzing Residuals.
22. Building Multiple Regression Models.
23. Multiple Regression Diagnostics.
APPENDICES.
A. Obtaining Charts in SPSS.
B. Transforming and Selecting Data.
C. The T Distribution.
D. Areas under the Normal Curve.
E. Descriptions of Data Files.
Bibliography.
Index.
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