Nonparametric Statistics for Non-Statisticians
A Step-by-Step Approach
(Sprache: Englisch)
A practical and understandable approach to nonparametric statistics for researchers across diverse areas of studyAs the importance of nonparametric methods in modern statistics continues to grow, these techniques are being increasingly applied to...
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A practical and understandable approach to nonparametric statistics for researchers across diverse areas of study
As the importance of nonparametric methods in modern statistics continues to grow, these techniques are being increasingly applied to experimental designs across various fields of study. However, researchers are not always properly equipped with the knowledge to correctly apply these methods. Nonparametric Statistics for Non-Statisticians: A Step-by-Step Approach fills a void in the current literature by addressing nonparametric statistics in a manner that is easily accessible for readers with a background in the social, behavioral, biological, and physical sciences.
Each chapter follows the same comprehensive format, beginning with a general introduction to the particular topic and a list of main learning objectives. A nonparametric procedure is then presented and accompanied by context-based examples that are outlined in a step-by-step fashion. Next, SPSS(r) screen captures are used to demonstrate how to perform and recognize the steps in the various procedures. Finally, the authors identify and briefly describe actual examples of corresponding nonparametric tests from diverse fields.
Using this organized structure, the book outlines essential skills for the application of nonparametric statistical methods, including how to:
* Test data for normality and randomness
* Use the Wilcoxon signed rank test to compare two related samples
* Apply the Mann-Whitney U test to compare two unrelated samples
* Compare more than two related samples using the Friedman test
* Employ the Kruskal-Wallis H test to compare more than two unrelated samples
* Compare variables of ordinal or dichotomous scales
* Test for nominal scale data
A detailed appendix provides guidance on inputting and analyzing the presented data using SPSS(r), and supplemental tables of critical values are provided. In addition, the book's FTP site houses supplemental data sets and solutions for further practice.
Extensively classroom tested, Nonparametric Statistics for Non-Statisticians is an ideal book for courses on nonparametric statistics at the upper-undergraduate and graduate levels. It is also an excellent reference for professionals and researchers in the social, behavioral, and health sciences who seek a review of nonparametric methods and relevant applications.
Klappentext zu „Nonparametric Statistics for Non-Statisticians “
A practical and understandable approach to nonparametric statistics for researchers across diverse areas of studyAs the importance of nonparametric methods in modern statistics continues to grow, these techniques are being increasingly applied to experimental designs across various fields of study. However, researchers are not always properly equipped with the knowledge to correctly apply these methods. Nonparametric Statistics for Non-Statisticians: A Step-by-Step Approach fills a void in the current literature by addressing nonparametric statistics in a manner that is easily accessible for readers with a background in the social, behavioral, biological, and physical sciences.
Each chapter follows the same comprehensive format, beginning with a general introduction to the particular topic and a list of main learning objectives. A nonparametric procedure is then presented and accompanied by context-based examples that are outlined in a step-by-step fashion. Next, SPSS(r) screen captures are used to demonstrate how to perform and recognize the steps in the various procedures. Finally, the authors identify and briefly describe actual examples of corresponding nonparametric tests from diverse fields.
Using this organized structure, the book outlines essential skills for the application of nonparametric statistical methods, including how to:
Test data for normality and randomness
Use the Wilcoxon signed rank test to compare two related samples
Apply the Mann-Whitney U test to compare two unrelated samples
Compare more than two related samples using the Friedman test
Employ the Kruskal-Wallis H test to compare more than two unrelated samples
Compare variables of ordinal or dichotomous scales
Test for nominal scale data
A detailed appendix provides guidance on inputting and analyzing the presented data using SPSS(r), and supplemental tables of critical values are provided. In addition, the book's FTP site houses supplemental data sets and solutions for further
... mehr
practice.
Extensively classroom tested, Nonparametric Statistics for Non-Statisticians is an ideal book for courses on nonparametric statistics at the upper-undergraduate and graduate levels. It is also an excellent reference for professionals and researchers in the social, behavioral, and health sciences who seek a review of nonparametric methods and relevant applications.
Extensively classroom tested, Nonparametric Statistics for Non-Statisticians is an ideal book for courses on nonparametric statistics at the upper-undergraduate and graduate levels. It is also an excellent reference for professionals and researchers in the social, behavioral, and health sciences who seek a review of nonparametric methods and relevant applications.
... weniger
This book fills a gap in the literature by addressing nonparametric statistics in a comprehensible manner that is ideal for social and health scientists. It is extensively classroom tested and proven to be effective for non-statisticians; it utilizes SPSS(r) to demonstrate how to perform the book's numerous examples in a step-by-step fashion; and presents a practical and understandable approach that enhances and expands the statistical toolset for readers.
Inhaltsverzeichnis zu „Nonparametric Statistics for Non-Statisticians “
PrefaceChapter 1: Nonparametric Statistics: An Introduction
1.1. Objectives
1.2. Introduction
1.3. The Nonparametric Statistical Procedures Presented In This Book
1.4. Ranking Data
1.5. Ranking Data with Tied Values
1.6. Counts Of Observations
1.7. Summary
1.8. Practice Questions
1.9 Solutions To Practice Questions
Chapter 2: Testing Your Data For Normality
2.1. Objectives
2.2. Introduction
2.3. Describing Data and The Normal Distribution
2.4. Computing And Testing Kurtosis And Skewness For Sample Normality
2.5. The Kolmogorov-Smirnov One-Sample Test
2.6. Summary
2.7. Practice Questions
2.8. Solutions To Practice Questions
Chapter 3: Comparing Two Related Samples: The Wilcoxon Signed Ranks Test
3.1. Objectives
3.2. Introduction
3.3. Computing The Wilcoxon Signed Ranks Test Statistic
3.4. Examples From The Literature
3.5. Summary
3.6. Practice Questions
3.7. Solutions To Practice Questions
Chapter 4: Comparing Two Unrelated Samples: The Mann-Whitney U Test
4.1. Objectives
4.2. Introduction
4.3. Computing The Mann-Whitney U Test Statistic
4.4. Examples From The Literature
4.5. Summary
4.6. Practice Questions
4.7. Solutions To Practice Questions
Chapter 5: Comparing More Than Two Related Samples: Friedman's Test
5.1. Objectives
5.2. Introduction
5.3. Computing The Friedman's Test Statistic
5.4. Examples From The Literature
5.5. Summary
5.6. Practice Questions
5.7. Solutions To Practice Questions
Chapter 6: Comparing More Than Two Unrelated Samples: Kruskal-Wallis H Test
6.1. Objectives
6.2. Introduction
6.3. Computing The Kruskal-Wallis H Test Statistic
6.4. Examples From The Literature
6.5. Summary
6.6. Practice Questions
6.7. Solutions To Practice Questions
Chapter 7: Comparing Variables Of Ordinal Or Dichotomous Scales: Spearman Rank-Order, Point-Biserial, And Biserial Correlations
7.1. Objectives
7.2.
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Introduction
7.3. The Correlation Coefficient
7.4. Computing The Spearman Rank-Order Correlation Coefficient
7.5. Computing the Point-Biserial and Biserial Correlation Coefficients
7.6. Examples From The Literature
7.7. Summary
7.8. Practice Questions
7.9. Solutions To Practice Questions
Chapter 8: Tests For Nominal Scale Data: Chi-Square Tests
8.1. Objectives
8.2. Introduction
8.3. The Chi-Square Goodness-of-Fit Test
8.4. Chi-Square Test Of Independence
8.5. The Fisher Exact Test
8.6. Examples From The Literature
8.7. Summary
8.8. Practice Questions
8.9. Solutions To Practice Questions
Chapter 9: Test For Randomness: Runs Test
9.1. Objectives
9.2. Introduction
9.3. The Runs Test For Randomness
9.4. Examples From The Literature
9.5. Summary
9.6. Practice Questions
9.7. Solutions To Practice Questions
Appendix A: SPSS at a Glance
A.1. Introduction
A.2. Opening SPSS
A.3. Inputting Data
A.4. Analyzing Data
A.5. The SPSS Output
Appendix B: Tables of Critical Values
Table B.1: The Normal Distribution
Table B.2: Chi-Squared Distribution
Table B.3: Critical Values for the Wilcoxon Signed Rank Test Statistics, T
Table B.4: Critical Values for the Mann-Whitney U Test Statistic
Table B.5: Critical Values for the Friedman Test Statistic, Fr
Table B.6: The Critical Values for the Kruskal-Wallis H Test Statistic
Table B.7: Critical Values for the Spearman Rank-Order Correlation Coefficient, rs
Table B.8: Critical Values for the Pearson Product-Moment Correlation Coefficient, r
Table B.9: Critical Values for the Fisher Exact Test
Table B.10: Critical Values for the Runs Test for Randomness
7.3. The Correlation Coefficient
7.4. Computing The Spearman Rank-Order Correlation Coefficient
7.5. Computing the Point-Biserial and Biserial Correlation Coefficients
7.6. Examples From The Literature
7.7. Summary
7.8. Practice Questions
7.9. Solutions To Practice Questions
Chapter 8: Tests For Nominal Scale Data: Chi-Square Tests
8.1. Objectives
8.2. Introduction
8.3. The Chi-Square Goodness-of-Fit Test
8.4. Chi-Square Test Of Independence
8.5. The Fisher Exact Test
8.6. Examples From The Literature
8.7. Summary
8.8. Practice Questions
8.9. Solutions To Practice Questions
Chapter 9: Test For Randomness: Runs Test
9.1. Objectives
9.2. Introduction
9.3. The Runs Test For Randomness
9.4. Examples From The Literature
9.5. Summary
9.6. Practice Questions
9.7. Solutions To Practice Questions
Appendix A: SPSS at a Glance
A.1. Introduction
A.2. Opening SPSS
A.3. Inputting Data
A.4. Analyzing Data
A.5. The SPSS Output
Appendix B: Tables of Critical Values
Table B.1: The Normal Distribution
Table B.2: Chi-Squared Distribution
Table B.3: Critical Values for the Wilcoxon Signed Rank Test Statistics, T
Table B.4: Critical Values for the Mann-Whitney U Test Statistic
Table B.5: Critical Values for the Friedman Test Statistic, Fr
Table B.6: The Critical Values for the Kruskal-Wallis H Test Statistic
Table B.7: Critical Values for the Spearman Rank-Order Correlation Coefficient, rs
Table B.8: Critical Values for the Pearson Product-Moment Correlation Coefficient, r
Table B.9: Critical Values for the Fisher Exact Test
Table B.10: Critical Values for the Runs Test for Randomness
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Autoren-Porträt von Gregory W. Corder, Dale I. Foreman
Gregory W. Corder is adjunct instructor of undergraduate physics and general science for the College of Science and Mathematics at James Madison University and adjunct instructor of graduate educational statistics for the School of Education and Human Development in the College of Arts and Sciences at Shenandoah University.Dale I. Foreman is associate professor in the School of Education and Human Development in the College of Arts and Sciences at Shenandoah University, where his teaching is focused on research, measurement, and statistics.
Bibliographische Angaben
- Autoren: Gregory W. Corder , Dale I. Foreman
- 2009, 1. Auflage, 264 Seiten, Maße: 16 x 23,6 cm, Gebunden, Englisch
- Verlag: Wiley & Sons
- ISBN-10: 047045461X
- ISBN-13: 9780470454619
Sprache:
Englisch
Rezension zu „Nonparametric Statistics for Non-Statisticians “
"This would be a very useful resource for courses in nonparametric statistics in which the emphasis is on applications rather than on theory. It also deserves a place in libraries of all institutions where introductory statistics courses are taught." (CHOICE, March 2010)
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