Introduction to Nonparametric Statistics for the Biological Sciences Using R
Author:   Thomas W. MacFarland ,  Jan M. Yates
Publisher:   Springer International Publishing AG
Edition:   1st ed. 2016
ISBN:  

9783319306339


Pages:   329
Publication Date:   16 July 2016
Format:   Hardback
Availability:   Manufactured on demand   Availability explained
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Introduction to Nonparametric Statistics for the Biological Sciences Using R


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Author:   Thomas W. MacFarland ,  Jan M. Yates
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   1st ed. 2016
Dimensions:   Width: 15.50cm , Height: 2.10cm , Length: 23.50cm
Weight:   6.447kg
ISBN:  

9783319306339


ISBN 10:   3319306332
Pages:   329
Publication Date:   16 July 2016
Audience:   College/higher education ,  Undergraduate ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Chapter 1 Nonparametric Statistics for the Biological Sciences.- Chapter 2 Sign Test.- Chapter 3 Chi-Square.- Chapter 4 Mann-Whitney U Test.- Chapter 5 Wilcoxon Matched-Pairs Signed-Ranks Test.- Chapter 6 Kruskal-Wallis H-Test for Oneway Analysis of Variance (ANOVA) by Ranks.- Chapter 7 Friedman Twoway Analysis of Variance (ANOVA) by Ranks.- Chapter 8 Spearman's Rank-Difference Coefficient of Correlation.- Chapter 9 Other Nonparametric Tests for the Biological Sciences.

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Author Information

Thomas W. MacFarland, Ed.D., is Associate Professor (Computer Technology) at Nova Southeastern University in Fort Lauderdale, Florida.  He joined the Graduate School of Computer and Information Sciences in 1988 and provides consulting services to the university community on research methods and statistical design as well as individual research on institutional concerns and assessment of student learning.  Dr. MacFarland's areas of research include institutional research, assessment of student learning outcomes, federal data resources, and K-12 computer science education. Jan Yates, Ph.D., is Associate Professor of Educational Media and Computer Science Education at Nova Southeastern University's Abraham S. Fischler College of Education in Fort Lauderdale, Florida. Since 2001, she has worked in the areas of curriculum development, program assessment and review, and accreditation.

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