Introduction to Nonparametric Statistics for the Biological Sciences Using R - Thomas W. MacFarland, Jan M. Yates

Introduction to Nonparametric Statistics for the Biological Sciences Using R

Buch | Softcover
XV, 329 Seiten
2018 | 1. Softcover reprint of the original 1st ed. 2016
Springer International Publishing (Verlag)
978-3-319-80856-7 (ISBN)
69,54 inkl. MwSt

This book contains a rich set of tools for nonparametric analyses, and the purpose of this text is to provide guidance to students and professional researchers on how R is used for nonparametric data analysis in the biological sciences:

  • To introduce when nonparametric approaches to data analysis are appropriate
  • To introduce the leading nonparametric tests commonly used in biostatistics and how R is used to generate appropriate statistics for each test
  • To introduce common figures typically associated with nonparametric data analysis and how R is used to generate appropriate figures in support of each data set

The book focuses on how R is used to distinguish between data that could be classified as nonparametric as opposed to data that could be classified as parametric, with both approaches to data classification covered extensively. Following an introductory lesson on nonparametric statistics for the biological sciences, the book is organized into eight self-contained lessons on various analyses and tests using R to broadly compare differences between data sets and statistical approach.

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.

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.

Erscheinungsdatum
Zusatzinfo XV, 329 p. 65 illus., 64 illus. in color.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Gewicht 534 g
Themenwelt Mathematik / Informatik Mathematik Computerprogramme / Computeralgebra
Mathematik / Informatik Mathematik Statistik
Mathematik / Informatik Mathematik Wahrscheinlichkeit / Kombinatorik
Medizin / Pharmazie
Weitere Fachgebiete Land- / Forstwirtschaft / Fischerei
Schlagworte Agriculture • ANOVA • biological sciences • Biostatistics • Biotechnology • Kruskal-Wallis H-Test • Life Sciences • Mann-Whitney U-Test • Nonparametric • Normal distribution • Oneway • plant science • R • Ranks • Wilcoxon Matched-Pairs Signed Ranks Test
ISBN-10 3-319-80856-7 / 3319808567
ISBN-13 978-3-319-80856-7 / 9783319808567
Zustand Neuware
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