Biostatistical Analysis 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. 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 For all readers interested in biostatistics. |
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User Review - LannyH - LibraryThingZar has always been my go-to reference for statistics. The book covers everything from distributional statistics and description to survival probabilities and above. As computer statistics programs ... Read full review
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Contents
OneSample Hypotheses | 7 |
Populations and Samples | 16 |
Measures of Variability and Dispersion | 33 |
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analysis analysis of variance angle animals ANOVA Appendix Table applied approximation associated binomial calculated called Chapter chi-square circular coefficient compared conclude confidence interval confidence limits cont contingency correlation coefficient Critical Values degrees of freedom demonstrated dependent described desired determine deviation direction discussed distribution effect employed equal Equation error estimate Example expressed factor females Figure four frequency given greater groups independent indicated larger least less linear males measurements median methods multiple namely nonparametric null hypothesis observed obtained one-tailed pair performed population population mean possible prediction present probability procedure proportion random range ranks ratio referred regression rejected relative sample scale Section shown significance situation sizes species specified standard statistical sum of squares term transformation two-tailed Type variable variance weight zero