Biostatistical analysis
著者
書誌事項
Biostatistical analysis
Pearson Education, c2010
5th ed
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注記
Included bibliographical references (p. 886-921) and index
内容説明・目次
内容説明
Zar's Biostatistical Analysis, Fifth Edition, is the ideal book for readers seeking practical coverage of statistical analysis methods used by researchers to collect, summarize, analyze and draw conclusions from biological research. The latest edition of this best-selling textbook is both comprehensive and easy to read. It is suitable as an introduction for beginners and as a comprehensive reference book for biological researchers and other advanced users.
KEY TOPICS: Introduction; Populations and Samples; Measures of Central Tendency; Measures of Dispersion and Variability; Probabilities; The Normal Distribution; One-Sample Hypotheses; Two-Sample Hypotheses; Paired-Sample Hypotheses; Multisample Hypotheses: The Analysis of Variance; Multiple Comparisons; Two-Factor Analysis of Variance; Data Transformations; Multiway Factorial Analysis of Variance; Nested (Hierarchical) Analysis of Variance; Multivariate Analysis of Variance; Simple Linear Regression; Comparing Simple Linear Regression Equations; Simple Linear Correlation; Multiple Regression and Correlation; Polynomial Regression; Testing for Goodness of Fit; Contingency Tables; More on Dichotomous Variables; Testing for Randomness; Circular Distributions: Descriptive Statistics; Circular Distributions: Hypothesis Testing
MARKET: For all readers interested in biostatistics.
目次
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
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