Statistics in plain English
著者
書誌事項
Statistics in plain English
Routledge, 2022
5th ed
- : hbk
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注記
Includes bibliographical references (p. 281-282), glossaries and index
Previous ed.: 2016
内容説明・目次
内容説明
* It is a straightforward, conversational introduction to statistics that delivers exactly what its title promises.
* Each chapter begins with a brief overview of a statistic that describes what the statistic does and when to use it, followed by a detailed step-by-step explanation of how the statistic works and exactly what information it provides.
* Chapters also include an example of the statistic (or statistics) in use in real-world research, "Worked Examples," "Writing It Up" sections that demonstrate how to write about each statistic, "Wrapping Up and Looking Forward" sections, and practice work problems.
* A new chapter on person-centered analyses, including cluster analysis and latent class analysis (LCA) has been added (Chapter 16).
* Person-centered analysis is an important alternative to the more commonly used variable-centered analyses (e.g., t tests, ANOVA, regression) and is gaining popularity in social-science research.
* The chapter on non-parametric statistics (Chapter 14) was enhanced significantly with in-depth descriptions of Mann-Whitney U, Kruskall-Wallace, and Wilcoxon Signed-Rank analyses.
* These non-parametric statistics are important alternatives to statistics that rely on normally distributed data.
* This new edition also includes more information about the assumptions of various statistics, including a detailed explanation of the assumptions and consequences of violating the assumptions of regression (Chapter 13).
* There is more information provided about the importance of the normal distribution in statistics (Chapters 4 and 7).
* Each of the last nine chapters includes an example from the real world of research that employs the statistic, or statistics, covered in the chapter.
* Altogether, these improvements provide important foundational information about how inferential statistics work and additional statistical tools that are commonly used by researchers in the social sciences.
* The text works as a standalone or as a supplement and covers a range of statistical concepts from descriptive statistics to factor analysis and person-centered analyses.
目次
1. Introduction to Social Science Research Principles and Terminology, 2. Measures of Central Tendency, 3. Measures of Variability, 4. The Normal Distribution, 5. Standardization and z Scores, 6. Standard Errors, 7. Statistical Significance, Effect Size, and Confidence Intervals, 8. t Tests, 9. One-Way Analysis of Variance, 10. Factorial Analysis of Variance, 11. Repeated-Measures Analysis of Variance, 12. Correlation, 13. Regression, 14. Nonparametric Statistics, 15. Factor Analysis and Reliability Analysis: Data Reduction Techniques, 16. Person-Centered Analysis, Appendix A. Area Under the Normal Curve Beyond Z, Appendix B. Critical Values of the t Distributions, Appendix C. Critical Values of the F Distributions, Appendix D. Critical Values of the Studentized Range Statistic (for Tukey HSD Tests), Appendix E: Table of the Fischer's Z Transformations for Correlation Coefficients, Appendix F. Critical Values of the Mann-Whitney U Statistic, Appendix G. Critical Values for Wilcoxon Signed-Rank Test, Appendix H. Critical Values of the X2 Distributions
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