Nonparametric statistics for non-statisticians : a step-by-step approach / Gregory W. Corder and Dale I. Foreman.
Material type:
- 9780470454619
- QA 278.8 .C67 2009

Item type | Current library | Home library | Collection | Call number | Copy number | Status | Date due | Barcode | |
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National University - Manila | LRC - Main General Circulation | Gen. Ed. - COE | GC QA 278.8 .C67 2009 (Browse shelf(Opens below)) | c.1 | Available | NULIB000008908 |
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GC QA 276.12 .S65 2008 Schaum's outline of theory and problems of statistics / | GC QA 276.12 .W45 1995 Introductory statistics / | GC QA 278.2 .W45 2014 Applied linear regression / | GC QA 278.8 .C67 2009 Nonparametric statistics for non-statisticians : a step-by-step approach / | GC QA 303.2 .L37 2010 Calculus / | GC QA 303.2 .S74 2012 Single variable calculus : early transcendentals / | GC QA 402.3 .R64 1993 Linear control systems / |
Includes bibliographical references and index.
"Nonparametric Statistics for Non-Statisticians: A Step-by-Step Approach"; "CONTENTS"; "Preface"; "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"; "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 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"; "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"; "3.3.1 Sample Wilcoxon Signed Ranks Test (Small Data Samples)"; "3.3.2 Performing the Wilcoxon Signed Ranks Test Using SPSS"; "3.3.3 Confidence Interval for the Wilcoxon Signed Ranks Test"; "3.3.4 Sample Wilcoxon Signed Ranks Test (Large Data Samples)"; "3.4 Examples from the Literature"; "3.5 Summary"; "3.6 Practice Questions"; "3.7 Solutions to Practice Questions"; "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""4.3.1 Sample Mann�Whitney U-Test (Small Data Samples)"; "4.3.2 Performing the Mann�Whitney U-Test Using SPSS"; "4.3.3 Confidence Interval for the Difference Between Two Location Parameters"; "4.3.4 Sample Mann�Whitney U-Test (Large Data Samples)"; "4.4 Examples from the Literature"; "4.5 Summary"; "4.6 Practice Questions"; "4.7 Solutions to Practice Questions"; "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 Test (Small Data Samples Without Ties)""5.3.2 Sample Friedman Test (Small Data Samples with Ties)"; "5.3.3 Performing the Friedman Test Using SPSS"; "5.3.4 Sample Friedman Test (Large Data Samples Without Ties)"; "5.4 Examples from the Literature"; "5.5 Summary"; "5.6 Practice Questions"; "5.7 Solutions to Practice Questions"; "6 Comparing More than Two Unrelated Samples: The Kruskal�Wallis H-Test"; "6.1 Objectives"; "6.2 Introduction"; "6.3 Computing the Kruskal�Wallis H-Test Statistic"
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.
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