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Nonparametric Statistics for Non-Statisticians: A Step-by-Step Approach Book

Nonparametric Statistics for Non-Statisticians: A Step-by-Step Approach
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Nonparametric Statistics for Non-Statisticians: A Step-by-Step Approach, 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 knowl, Nonparametric Statistics for Non-Statisticians: A Step-by-Step Approach
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  • Nonparametric Statistics for Non-Statisticians: A Step-by-Step Approach
  • Written by author Gregory W. Corder
  • Published by Wiley, John & Sons, Incorporated, 9/20/2011
  • 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 knowl
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2.5 The Kolmogorov-Smirnov One-Sample Test 26

2.5.1 Sample Kolmogorov-Smirnov One-Sample Test 28

2.5.2 Performing the Kolmogorov-Smirnov One-Sample Test Using SPSS 32

2.6 Summary 35

2.7 Practice Questions 35

2.8 Solutions to Practice Questions 36

3 Comparing Two Related Samples: The Wilcoxon Signed Ranks Test 38

3.1 Objectives 38

3.2 Introduction 38

3.3 Computing the Wilcoxon Signed Ranks Test Statistic 39

3.3.1 Sample Wilcoxon Signed Ranks Test (Small Data Samples) 40

3.3.2 Performing the Wilcoxon Signed Ranks Test Using SPSS 42

3.3.3 Confidence Interval for the Wilcoxon Signed Ranks Test 45

3.3.4 Sample Wilcoxon Signed Ranks Test (Large Data Samples) 47

3.4 Examples from the Literature 51

3.5 Summary 51

3.6 Practice Questions 52

3.7 Solutions to Practice Questions 55

4 Comparing Two Unrelated Samples: The Mann-Whitney U-Test 57

4.1 Objectives 57

4.2 Introduction 57

4.3 Computing the Mann-Whitney U-Test Statistic 58

4.3.1 Sample Mann-Whitney U-Test (Small Data Samples) 59

4.3.2 Performing the Mann-Whitney U-Test Using SPSS 62

4.3.3 Confidence Interval for the Difference Between Two Location Parameters 66

4.3.4 Sample Mann-Whitney U-Test (Large Data Samples) 68

4.4 Examples from the Literature 72

4.5 Summary 74

4.6 Practice Questions 74

4.7 Solutions to Practice Questions 77

5 Comparing More Than Two Related Samples: The Friedman Test 79

5.1 Objectives 79

5.2 Introduction 79

5.3 Computing the Friedman Test Statistic 80

5.3.1 Sample Friedman Test (Small Data Samples Without Ties) 81

5.3.2 Sample Friedman Test (Small Data Samples with Ties) 84

5.3.3 Performing the Friedman Test Using SPSS 88

5.3.4 SampleFriedman Test (Large Data Samples Without Ties) 90

5.4 Examples from the Literature 93

5.5 Summary 95

5.6 Practice Questions 95

5.7 Solutions to Practice Questions 96

6 Comparing More than Two Unrelated Samples: The Kruskal-Wallis H-Test 99

6.1 Objectives 99

6.2 Introduction 99

6.3 Computing the Kruskal-Wallis H-Test Statistic 100

6.3.1 Sample Kruskal-Wallis H-Test (Small Data Samples) 101

6.3.2 Performing the Kruskal-Wallis H-Test Using SPSS 106

6.3.3 Sample Kruskal-Wallis H-Test (Large Data Samples) 110

6.4 Examples from the Literature 116

6.5 Summary 117

6.6 Practice Questions 117

6.7 Solutions to Practice Questions 118

7 Comparing Variables of Ordinal or Dichotomous Scales: Spearman Rank-Order, Point-Biserial, and Biserial Correlations 122

7.1 Objectives 122

7.2 Introduction 122

7.3 The Correlation Coefficient 123

7.4 Computing the Spearman Rank-Order Correlation Coefficient 124

7.4.1 Sample Spearman Rank-Order Correlation (Small Data Samples Without Ties) 125

7.4.2 Sample Spearman Rank-Order Correlation (Small Data Samples with Ties) 128

7.4.3 Performing the Spearman Rank-Order Correlation Using SPSS 131

7.5 Computing the Point-Biserial and Biserial Correlation Coefficients 134

7.5.1 Correlation of a Dichotomous Variable and an Interval Scale Variable 134

7.5.2 Correlation of a Dichotomous Variable and a Rank-Order Variable 136

7.5.3 Sample Point-Biserial Correlation (Small Data Samples) 136

7.5.4 Performing the Point-Biserial Correlation Using SPSS 139

7.5.5 Sample Point-Biserial Correlation (Large Data Samples) 142

7.5.6 Sample Biserial Correlation (Small Data Samples) 146

7.5.7 Performing the Biserial Correlation Using SPSS 149

7.6 Examples from the Literature 150

7.7 Summary 151

7.8 Practice Questions 151

7.9 Solutions to Practice Questions 154

8 Tests for Nominal Scale Data: Chi-Square and Fisher Exact Test 155

8.1 Objectives 155

8.2 Introduction 155

8.3 The Chi-Square Goodness-of-Fit Test 156

8.3.1 Computing the Chi-Square Goodness-of-Fit Test Statistic 156

8.3.2 Sample Chi-Square Goodness-of-Fit Test (Category Frequencies Equal) 157

8.3.3 Sample Chi-Square Goodness-of-Fit Test (Category Frequencies Not Equal) 160

8.3.4 Performing the Chi-Square Goodness-of-Fit Test Using SPSS 163

8.4 The Chi-Square Test for Independence 167

8.4.1 Computing the Chi-Square Test for Independence 168

8.4.2 Sample Chi-Square Test for Independence 169

8.4.3 Performing the Chi-Square Test for Independence Using SPSS 174

8.5 The Fisher Exact Test 179

8.5.1 Computing the Fisher Exact Test for 2 x 2 Tables 180

8.5.2 Sample Fisher Exact Test 180

8.5.3 Performing the Fisher Exact Test Using SPSS 184

8.6 Examples from the Literature 185

8.7 Summary 187

8.8 Practice Questions 187

8.9 Solutions to Practice Questions 189

9 Test For Randomness: The Runs Test 192

9.1 Objectives 192

9.2 Introduction 192

9.3 The Runs Test for Randomness 193

9.3.1 Sample Runs Test (Small Data Samples) 194

9.3.2 Performing the Runs Test Using SPSS 195

9.3.3 Sample Runs Test (Large Data Samples) 200

9.3.4 Sample Runs Test Referencing a Custom Value 202

9.3.5 Performing the Runs Test for a Custom Value Using SPSS 204

9.4 Examples from the Literature 208

9.5 Summary 209

9.6 Practice Questions 209

9.7 Solutions to Practice Questions 210

Appendix A SPSS at a Glance 212

A.1 Introduction 212

A.2 Opening SPSS 212

A.3 Inputting Data 212

A.4 Analyzing Data 216

A.5 The SPSS Output 217

Bibliography 243

Index 245


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Nonparametric Statistics for Non-Statisticians: A Step-by-Step Approach, 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 knowl, Nonparametric Statistics for Non-Statisticians: A Step-by-Step Approach

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Nonparametric Statistics for Non-Statisticians: A Step-by-Step Approach, 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 knowl, Nonparametric Statistics for Non-Statisticians: A Step-by-Step Approach

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Nonparametric Statistics for Non-Statisticians: A Step-by-Step Approach, 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 knowl, Nonparametric Statistics for Non-Statisticians: A Step-by-Step Approach

Nonparametric Statistics for Non-Statisticians: A Step-by-Step Approach

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