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Nonparametric statistics : a step-by-step approach

Author: Gregory W Corder; Dale I Foreman
Publisher: Hoboken, New Jersey : John Wiley & Sons, [2014]
Edition/Format:   eBook : Document : English : Second editionView all editions and formats
Summary:
"This Second Edition presents nonparametric statistical procedures in a clear manner and was specifically written for readers with a background in the social, behavioral, and health sciences. The book continues to follow the same format in all chapters to aid in reader comprehension, and each chapter begins with a general introduction and a list of the chapter's main learning objectives. A nonparametric procedure is
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Corder, Gregory W., 1972-
Nonparametric statistics.
Hoboken, New Jersey : John Wiley & Sons, Inc., [2014]
(DLC) 2013042040
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Gregory W Corder; Dale I Foreman
ISBN: 9781118840429 1118840429 9781118840320 1118840321 9781118840405 1118840402 1118840313 9781118840313 9781306892674 1306892678
OCLC Number: 862222362
Description: 1 online resource
Contents: Cover --
Title page --
Copyright page --
Contents --
Preface --
List of Variables --
CHAPTER 1: Nonparametric Statistics: An Introduction --
1.1 Objectives --
1.2 Introduction --
1.3 The Nonparametric Statistical Procedures Presented in this Book --
1.3.1 State the Null and Research Hypotheses --
1.3.2 Set the Level of Risk (or the Level of Significance) Associated with the Null Hypothesis --
1.3.3 Choose the Appropriate Test Statistic --
1.3.4 Compute the Test Statistic --
1.3.5 Determine the Value Needed for Rejection of the Null Hypothesis Using the Appropriate Table of Critical Values for the Particular Statistic --
1.3.6 Compare the Obtained Value with the Critical Value --
1.3.7 Interpret the Results --
1.3.8 Reporting the Results --
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 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 --
2.4.1 Sample Problem for Examining Kurtosis --
2.4.2 Sample Problem for Examining Skewness --
2.4.3 Examining Skewness and Kurtosis for Normality Using SPSS --
2.5 Computing the Kolmogorov-Smirnov One-Sample Test --
2.5.1 Sample Kolmogorov-Smirnov One-Sample Test --
2.5.2 Performing the Kolmogorov-Smirnov One-Sample Test Using SPSS --
2.6 Summary --
2.7 Practice Questions --
2.8 Solutions to Practice Questions --
CHAPTER 3: Comparing Two Related Samples: The Wilcoxon Signed Rank and the Sign Test --
3.1 Objectives --
3.2 Introduction --
3.3 Computing the Wilcoxon Signed Rank Test Statistic --
3.3.1 Sample Wilcoxon Signed Rank Test (Small Data Samples) --
3.3.2 Confidence Interval for the Wilcoxon Signed Rank Test. 3.3.3 Sample Wilcoxon Signed Rank Test (Large Data Samples) --
3.4 Computing the Sign Test --
3.4.1 Sample Sign Test (Small Data Samples) --
3.4.2 Sample Sign Test (Large Data Samples) --
3.5 Performing the Wilcoxon Signed Rank Test and the Sign Test Using SPSS --
3.5.1 Define Your Variables --
3.5.2 Type in Your Values --
3.5.3 Analyze Your Data --
3.5.4 Interpret the Results from the SPSS Output Window --
3.6 Statistical Power --
3.7 Examples from the Literature --
3.8 Summary --
3.9 Practice Questions --
3.10 Solutions to Practice Questions --
CHAPTER 4: Comparing Two Unrelated Samples: The Mann−Whitney U-Test and the Kolmogorov−Smirnov Two-Sample Test --
4.1 Objectives --
4.2 Introduction --
4.3 Computing the Mann−Whitney U-Test Statistic --
4.3.1 Sample Mann−Whitney U-Test (Small Data Samples) --
4.3.2 Confidence Interval for the Difference between Two Location Parameters --
4.3.3 Sample Mann−Whitney U-Test (Large Data Samples) --
4.4 Computing the Kolmogorov-Smirnov Two-Sample Test Statistic --
4.4.1 Sample Kolmogorov-Smirnov Two-Sample Test --
4.5 Performing the Mann-Whitney U-Test and the Kolmogorov-Smirnov Two-Sample Test Using SPSS --
4.5.1 Define Your Variables --
4.5.2 Type in Your Values --
4.5.3 Analyze Your Data --
4.5.4 Interpret the Results from the SPSS Output Window --
4.6 Examples from the Literature --
4.7 Summary --
4.8 Practice Questions --
4.9 Solutions to Practice Questions --
CHAPTER 5: Comparing More Than Two Related Samples: The Friedman Test --
5.1 Objectives --
5.2 Introduction --
5.3 Computing the Friedman Test Statistic --
5.3.1 Sample Friedman's Test (Small Data Samples without Ties) --
5.3.2 Sample Friedman's Test (Small Data Samples with Ties) --
5.3.3 Performing the Friedman Test Using SPSS --
5.3.4 Sample Friedman's Test (Large Data Samples without Ties) --
5.4 Examples from the Literature --
5.5 Summary.
Responsibility: Gregory W. Corder, Department of Physics and Astronomy, James Madison University, Harrisonburg, VA, Dale I. Foreman, Department of Research and Social Analysis, Shenandoah University, Winchester, VA.

Abstract:

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  Read more...

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