Biostatistical Analysis: International Edition
Autor Jerrold H Zaren Limba Engleză Paperback – 31 iul 2007
This book is appropriate for a one- or two-semester, junior or graduate-level course in biostatistics, biometry, quantitative biology, or statistics, and assumes a prerequisite of algebra.
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Specificații
ISBN-13: 9780132065023
ISBN-10: 0132065029
Pagini: 960
Dimensiuni: 203 x 254 x 30 mm
Greutate: 1.45 kg
Ediția:5Nouă
Editura: Pearson Education
Colecția Pearson Education
Locul publicării:Upper Saddle River, United States
ISBN-10: 0132065029
Pagini: 960
Dimensiuni: 203 x 254 x 30 mm
Greutate: 1.45 kg
Ediția:5Nouă
Editura: Pearson Education
Colecția Pearson Education
Locul publicării:Upper Saddle River, United States
Cuprins
1. Introduction
2. Populations and Samples
3. Measures of Central Tendency
4. Measures of Dispersion and Variability
5. Probabilities
6. The Normal Distribution
7. One-Sample Hypotheses
8. Two-Sample Hypotheses
9. Paired-Sample Hypotheses
10. Multisample Hypotheses: 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. More on Dichotomous Variables
25. Testing for Randomness
26. Circular Distributions: Descriptive Statistics
27. Circular Distributions: Hypothesis Testing
Appendix A: Analysis of Variance Hypothesis Testing
Appendix B: Statistical Tables and Graphs
Answers to Exercises
Literature Cited
Index
2. Populations and Samples
3. Measures of Central Tendency
4. Measures of Dispersion and Variability
5. Probabilities
6. The Normal Distribution
7. One-Sample Hypotheses
8. Two-Sample Hypotheses
9. Paired-Sample Hypotheses
10. Multisample Hypotheses: 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. More on Dichotomous Variables
25. Testing for Randomness
26. Circular Distributions: Descriptive Statistics
27. Circular Distributions: Hypothesis Testing
Appendix A: Analysis of Variance Hypothesis Testing
Appendix B: Statistical Tables and Graphs
Answers to Exercises
Literature Cited
Index
Notă biografică
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. Then, Zar returned to serve Northern Illinois University for 34 years 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-time 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-President for Graduate Studies and Research as well as the Dean of the Graduate School. He is a founding member 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 NIU and across the state. Zar is a member of 17 professional scientific societies, including the highly regarded American Association for the Advancement of Science. His fields of interests include statistical analysis of biological data and the physiological adaptations of animals to their environment.
Caracteristici
- A broad collection of data-analysis procedures and techniques are presented, covering a wide variety of biological research, such as physiology, genetics, ecology, behavior, morphology.
- The most comprehensive treatment available includes coverage of the following unique topics.
- Diversity
- Polynomial regression
- Multidimensional contingency tables
- Stepwise regression
- Nonparametric multiple comparisons
- Higher order factorial analyses of variance
- Circular distributions
- Power and sample size determinations.
- An orderly organization and presentation of topics, with cross-referencing as appropriate.
- The 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.
- The exposition considers factorial analysis of variance and multiple regression in terms of the interpretation of typical computer output.
- A wealth of graphs and other figures are integrated to visually support concepts under discussion.
- A uniquely comprehensive set of statistical tables–more than 40 in all–facilitates statistical analyses without having to consult a separate book. This includes tables that are unique to this book.
- Worked examples for all major procedures guide readers step-by-step through the techniques, demonstrating each of the important concepts.
- An extensive bibliography directs readers for further research.
Caracteristici noi
This edition includes revised, updated, or enhanced coverage of the following topics.
- 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