This monograph develops stochastic models for describing and analyzing populations composed of a large number of classes, with primary emphasis on biological communities and species diversity. The book introduces both fixed and random population models and examines sampling theory, abundance distributions, and indices of diversity and equitability. Classical models such as Fisher’s logarithmi…
A classic textbook on statistical methods in biology, covering experimental design, data analysis, and application of biostatistical techniques to biological research.
A practical guide to the statistical techniques used by biologists in experimental design, data analysis, and result interpretation. This updated second edition includes examples using Excel and MINITAB, and is intended for students and researchers in the life sciences.
Understanding Biostatistics by Sharad Srivastava is an introductory textbook aimed at medical, biological, and health science students. It covers fundamental concepts of biostatistics such as descriptive statistics, probability distributions, hypothesis testing, linear regression, ANOVA, and survival analysis in a medical context. Emphasizing clarity over technical depth, it uses diagrams and s…
Student-focused introduction to statistics in biosciences; includes descriptive & inferential methods, regression, correlation, GLMs, plus student exercises and online SPSS/R screencasts. 4th ed. updates content and digital resources
A comprehensive undergraduate/postgraduate textbook on biostatistics, covering basics such as descriptive statistics, probability & distributions, sampling methods, inference, small and large sample tests, chi-square, non-parametric tests, ANOVA, regression, correlation, and experimental design. The second edition emphasizes clear illustrations, step-by-step explanations, and exercise-driven le…
This second edition offers a comprehensive examination of statistical methods applicable to bioassay, with emphasis on dose-response relationships, parallel line assays, and probit/logit analysis. It is an essential reference for pharmacologists, statisticians, and researchers involved in experimental biology.