Topics in Biostatistics

  • Walter T. Ambrosius

Part of the Methods in Molecular Biology™ book series (MIMB, volume 404)

Table of contents

  1. Front Matter
    Pages i-xii
  2. Hyun Ja Lim, Raymond G. Hoffmann
    Pages 1-17
  3. Raymond G. Hoffmann, Hyun Ja Lim
    Pages 19-31
  4. Todd G. Nick
    Pages 33-52
  5. Susan M. Perkins
    Pages 73-88
  6. Todd A. Alonzo, Margaret Sullivan Pepe
    Pages 89-116
  7. Nancy Berman
    Pages 117-142
  8. Lynn E. Eberly
    Pages 143-164
  9. Lynn E. Eberly
    Pages 165-187
  10. Edward H. Ip
    Pages 189-211
  11. Ann L. Oberg, Douglas W. Mahoney
    Pages 213-234
  12. Jonathan J. Shuster
    Pages 235-259
  13. James J. Grady
    Pages 261-271
  14. Todd G. Nick, Kathleen M. Campbell
    Pages 273-301
  15. Hongyu Jiang, Jason P. Fine
    Pages 303-318
  16. Mark E. Glickman, David A. van Dyk
    Pages 319-338
  17. Ralph B. D’Agostino Jr.
    Pages 339-352
  18. Curtis A. Parvin
    Pages 353-375
  19. L. Douglas Case, Walter T. Ambrosius
    Pages 377-408

About this book

Introduction

Biostatistics can be a language nearly indecipherable to those not trained to speak it.  In Topics in Biostatistics, a broad survey of biostatiscal methods, techniques are illustrated by clear, step-by-step instructions able to be performed with paper, a pencil, and a calculator. With subjects as diverse as descriptive statistics, study design, statistical inference, and linear and logistic regression, this volume invites the reader to better understand the language of statistics to aid in collaborations with biostatisticians or the deciphering of software manuals. Following the format of the highly successful Methods in Molecular Biology™ format, each protocol offers readily reproducible results, and, specifically in this case, provides the reader with a concise introduction to complicated statistical methods.

Comprehensive and enlightening, Topics in Biostatistics is the perfect statistical resource for scientists in all disciplines attempting to comprehend this challenging mathematical field.

Keywords

Radiologieinformationssystem bioinformatics biostatistics cancer classification descriptive statistics development evaluation genetics genome genome mapping informatics linear regression microarray statistics

Editors and affiliations

  • Walter T. Ambrosius
    • 1
  1. 1.Department of Biostatistical SciencesWake Forest University Health SciencesWinston-Salem

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-59745-530-5
  • Copyright Information Humana Press 2007
  • Publisher Name Humana Press
  • eBook Packages Springer Protocols
  • Print ISBN 978-1-58829-531-6
  • Online ISBN 978-1-59745-530-5
  • Series Print ISSN 1064-3745
  • Series Online ISSN 1940-6029
  • About this book