Biostatistical Analysis

Description

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 D: Analysis of Variance Hypothesis Testing

Answers to Exercises

Literature Cited

Author Index

Subject Index

New and updated features of this title

Revised, updated or enhanced coverage of:

• Normal distribution
• Testing for normality
• Power in statistical hypothesis testing
• The underlying assumptions, and their violation, in parametric and nonparametric testing
• A new introduction of prediction limits and one-tailed confidence limits
• Analysis of variance
• Comparing variances
• Multiple-comparison testing, emphasizing the most highly regarded procedures
• Randomized-block, repeated-measures, and multivariate analysis of variance
• Simple and multiple linear regression and correlation
• Kolmogorov-Smirnov goodness-for-fit testing for ordinal data, both two-tailed and one-tailed, continuous and discrete
• Contingency-table analysis by chi-square and the Fisher Exact Test
• The use of binomial distribution

Hallmark features of this title

• A broad collection of data-analysis procedures and techniques cover a wide variety of biological research, such as physiology, genetics, ecology, behavior, morphology.
• The most comprehensive treatment available includes coverage of the basics of statistical analysis, along with topics rarely or never found in statistics books for biologists including diversity, polynomial regression, and more.
• An orderly organization and presentation of topics includes cross-referencing as appropriate.
• A readable and accessible approach allows students with no previous statistical background or mathematical expertise beyond simple algebra to understand the material presented.
• The thoughtful presentation encourages students to think about the value of each statistical technique, as opposed to merely plugging numbers into formulae.
• A wealth of graphs and other figures are integrated to visually support concepts under discussion.

About our author

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 2 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. Zar is a member of 17 professional scientific societies, including an elected fellow of the American Association for the Advancement of Science. His many research publications cover a range of topics, from statistical analysis to physiological adaptations of animals to their environment.