Hand Book Of Research Methodology Biostatistics Mcqs
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Hand Book Of Research Methodology & Biostatistics Mcqs
Author: Dr. MUKESH KUMAR BISEN
language: en
Publisher: OrangeBooks Publication
Release Date: 2020-10-28
This in mind this book is written to prepare the students for the questions that are most frequently asked in various competitive exams along with important ones. Where ever need is felt the answer has been elaborated to make it more clear and understandable. Therefore all the students preparing for various tests like PG, PhD research officer & competitive exam will find this book immensely helpful. Silent fractures 1. MCQ from recent competitive exam. 2. Self test series has been included
ESSENTIALS OF BIOSTATISTICS AND RESEARCH METHODOLOGY
THIS TEXTBOOK IS A COMPREHENSIVE USER FRIENDLY AND EASY TO READ RESOURCE ON BIOSTATISTICS AND RESEARCH METHODOLOGY. IT IS MEANT FOR UNDERGRADUATE AND POSTGRADUATE MEDICAL STUDENTS AND ALLIED BIOMEDICAL SCIENCES. HEALTH RESEARCHERS, RESEARCH SUPERVISORS AND FACULTY MEMBERS MAY FIND IT USEFUL AS A REFERENCE BOOK
TEXT BOOK OF BIOSTATISTICS AND RESEARCH METHODOLOGY
Author: Dr. Kapil Pal, Dr. Nidhi Sharma, Dr. Abhishek Dwivedi, Dr. Dipanwita Chaudhuri Sil; Dr. Rupesh Kumar Mani
language: en
Publisher: Shashwat Publication
Release Date: 2025-04-25
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 regression modeling explains hypothesis testing in simple and multiple regression models, incorporating industrial and clinical trial applications using Excel, SPSS, MINITAB®, and R software. It also introduces the Design and Analysis of Experiments, with factorial designs, response surface methodology, and optimization techniques. With its structured approach, practical pharmaceutical examples, and in-depth statistical concepts, this textbook is an essential resource for students and professionals involved in biostatistics, clinical research, and pharmaceutical industry applications.