TEXT BOOK OF BIOSTATISTICS AND RESEARCH METHODOLOGY

About Book

The Textbook of Biostatistics and Research Methodology is a comprehensive guide designed for students, researchers, and professionals in pharmaceutical and biomedical sciences. It provides fundamental concepts and practical applications of statistical methods used in research and industry. The book begins with measures of central tendency, covering mean, median, and mode with pharmaceutical examples, helping readers understand data distribution in research. It then explores measures of dispersion, including range and standard deviation, which are crucial for analyzing variability in drug formulations and clinical studies. A dedicated section on correlation explains Karl Pearson’s coefficient and multiple correlation techniques, providing real-world pharmaceutical applications. The regression analysis chapter covers curve fitting, least squares method, and multiple regression, aiding in predictive modeling of drug responses. The book delves into probability distributions, including binomial, normal, and Poisson distributions, along with sampling techniques, hypothesis testing, and standard error concepts used in pharmaceutical research. Parametric tests, such as t-tests, ANOVA, and least significance difference methods, are thoroughly explained for comparing sample groups in clinical trials. For non-parametric analysis, tests like the Wilcoxon Rank Sum Test, Mann-Whitney U Test, Kruskal-Wallis Test, and Friedman Test are covered, offering alternatives for non-normally distributed data. The introduction to research methodology discusses the importance of experimental design, plagiarism, and ethical research practices. The book also covers graphical data representation through histograms, pie charts, cubic graphs, response surface plots, and contour plots, enhancing statistical analysis visualization. The methodology design chapter includes sample size determination, data presentation, and protocol development for cohort and clinical studies. A section on regress