Biostatistical Analysis (Classic Version)
5th Edition
Published on 21. March 2018
Book
Paperback/Softback
960 pages
978-0-13-499544-1 (ISBN)
Description
For a one- or two-semester, junior or graduate-level course in biostatistics Biostatistical Analysis is the ideal textbook for graduate and undergraduate students seeking practical coverage of statistical analysis methods used by researchers to collect, summarise, analyse and draw conclusions from biological research. This edition of this best-selling textbook is both comprehensive and easy to read. It is suitable as an introduction for beginning students and as a comprehensive reference book for biological researchers and for advanced students.
This book is appropriate for courses in biostatistics, biometry, quantitative biology, or statistics, and assumes a prerequisite of algebra.
This book is appropriate for courses in biostatistics, biometry, quantitative biology, or statistics, and assumes a prerequisite of algebra.
More details
Series
Edition
5th edition
Language
English
Place of publication
United States
Publishing group
Pearson Education (US)
Target group
College/higher education
Dimensions
Height: 255 mm
Width: 205 mm
Thickness: 46 mm
Weight
1880 gr
ISBN-13
978-0-13-499544-1 (9780134995441)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Previous edition
Jerrold Zar
Biostatistical Analysis
Loose-leaf edition
06/2010
5th Edition
Pearson
€171.71
Article exhausted; check for reprint
Person
Jerrold H. Zar received his undergraduate degree in Biological Sciences from Northern Illinois University in 1962. He later earned his M.S. and Ph.D. degrees in biology and zoology from the University of Illinois at Urbana-Champaign. Zar then returned to Northern Illinois University for 34 years to serve in a variety of capacities. He joined the faculty at NIU as an Assistant Professor in 1968 and quickly rose through the ranks of associate and full professor to become Chair of the Department of Biological Sciences in 1978. He served two terms as Chair of the Department and then, became the Vice Provost for Graduate Studies and Research and Dean of the Graduate School. He was a founder of the Illinois Minority Graduate Incentive Program and the Illinois Consortium for Educational Opportunities Program, where he helped create and protect fellowship opportunities for minority graduate students at universities across the state. His many research publications cover a range of topics, from statistical analysis to physiological adaptations of animals to their environment.
Content
1. Data: Types and Presentations
2. Populations and Samples
3. Measures of Central Tendency
4. Measures of Variability and Dispersion
5. Probabilities
6. The Normal Distribution
7. One-Sample Hypotheses
8. Two-Sample Hypotheses
9. Paired-Sample Hypotheses
10. Multisample Hypotheses and the Analysis of Variance
11. Multiple Comparisons
12. Two-Factor Analysis of Variance
13. Data Transformations
14. Multiway Factorial Analysis of Variance
15. Nested (Hierarchical) Analysis of Variance
16. Multivariate Analysis of Variance
17. Simple Linear Regression
18. Comparing Simple Linear Regression Equations
19. Simple Linear Correlation
20. Multiple Regression and Correlation
21. Polynomial Regression
22. Testing for Goodness of Fit
23. Contingency Tables
24. Dichotomous Variables
25. Testing for Randomness
26. Circular Distributions: Descriptive Statistics
27. Circular Distributions: Hypothesis Testing
Appendix A: The Greek Alphabet
Appendix B: Statistical Tables and Graphs
Appendix C: The Effects of Coding Data
Appendix B: Analysis of Variance Hypothesis Testing
Answers to Exercises
Literature Cited
Author Index
Subject Index
2. Populations and Samples
3. Measures of Central Tendency
4. Measures of Variability and Dispersion
5. Probabilities
6. The Normal Distribution
7. One-Sample Hypotheses
8. Two-Sample Hypotheses
9. Paired-Sample Hypotheses
10. Multisample Hypotheses and the Analysis of Variance
11. Multiple Comparisons
12. Two-Factor Analysis of Variance
13. Data Transformations
14. Multiway Factorial Analysis of Variance
15. Nested (Hierarchical) Analysis of Variance
16. Multivariate Analysis of Variance
17. Simple Linear Regression
18. Comparing Simple Linear Regression Equations
19. Simple Linear Correlation
20. Multiple Regression and Correlation
21. Polynomial Regression
22. Testing for Goodness of Fit
23. Contingency Tables
24. Dichotomous Variables
25. Testing for Randomness
26. Circular Distributions: Descriptive Statistics
27. Circular Distributions: Hypothesis Testing
Appendix A: The Greek Alphabet
Appendix B: Statistical Tables and Graphs
Appendix C: The Effects of Coding Data
Appendix B: Analysis of Variance Hypothesis Testing
Answers to Exercises
Literature Cited
Author Index
Subject Index