Biostatistical Methods and Applications

Experiment Design, Analysis, and Presenting Findings
Erscheinungsjahr 2026
ISBN: 978-0-443-33722-2
Verlag: Elsevier Science & Technology

Buch, Englisch, Format (B × H): 191 mm x 235 mm

Biostatistical Methods and Applications: Experiment Design, Analysis, and Presenting Findings provides students and researchers with the skills needed to apply biostatistical concepts and implement a wide range of analytical tools. The text is an accessible and intentionally curated resource that instructs readers in designing experiments, considering the results, and presenting statistical findings and views. In twenty-four chapters and additional appendices, the book starts with an introduction to the field of statistics and from there covers experiment design, data coding, and data collection methods. The book also delves into descriptive statistics, probability, statistical distributions, correlations, and regression. Common research techniques such as normality tests, sample size determination, missing data analysis, statistical inference, test of significance, and ANOVA are explained in a clear manner so that readers can successfully understand and apply these methods. Biostatistical Methods and Applications: Experiment Design, Analysis, and Presenting Findings thoroughly explores fundamental topics in biostatistics to guide readers in conducting statistical analysis and interpretation by using the step-by-step procedures and diagrams in the book. This book covers current topics which are being used frequently in teaching and research areas, as well as specific statistical techniques including multivariate analysis, binary logistic regression, and non-parametric methods. This valuable first edition provides the necessary tools and conceptual foundations in quantitative reasoning to efficiently extract information from a vast sea of data, and to communicate research findings in order to support hypotheses and give credibility to research methodology and conclusions. With detailed explanations, illustrative examples and diagrams, and beneficial in-text exercises and solutions to support the study of biostatistics, this textbook will prove useful to students, researchers, and scientists who aim to increase their precision around methods and techniques in this field.

Autoren/Hrsg.

Chaudhary, Jitendra Kumar

Fachgebiete

• Naturwissenschaften Physik Angewandte Physik Biophysik
• Naturwissenschaften Biowissenschaften Biochemie (nichtmedizinisch)

Inhaltsverzeichnis

1. Introduction
2. Questionnaire formats and Data Coding used for Epidemiological Survey Questionnaires
3. Data Presentation
4. Descriptive Statistics
5. Probability
6. Normality Tests and Data Transformation
7. Introduction to Sampling
8. Missing data mechanism
9. Statistical Inferences
10. Test of Significance
11. Correlation and Regression
12. Analysis of Variance (ANOVA)
13. Design of Experiments
14. Multivariate Analysis
15. Binary Logistic Regression
16. Nonparametric Methods
17. Observational Studies
18. Incidence, Prevalence and Risk
19. Odds and Odds Ratio
20. Cox Regression
21. Receiver Operating Characteristic (ROC) Curve
22. Survival Analysis (Kaplan-Meier Curves)
23. Heat Maps and Circos Plot
24. Path Coefficients

Über Autor(innen)

Chaudhary, Jitendra Kumar
Dr. J. K. Chaudhary graduated with his Masters in Veterinary Science in Biostatistics (2012) and Ph.D in Biostatistics (2015), from the Indian Veterinary Research Institute (IVRI) in Uttar Pradesh, India. Dr. Chaudhary qualified for the Indian Council of Agricultural Research-Junior Research Fellowship for Post-Graduates, the ICAR-Senior Research Fellowship, and the DBT- INSPIRE Fellowship for Ph.D. students. He started his current role as Assistant Professor in Animal Genetics and Breeding in the Biostatistics department at College of Veterinary Sciences and Animal Husbandry at Central Agricultural University in Mizoram, India in 2015. There, he managed two extramural research projects and two intramural research projects to date. Dr. Chaudary guided three Masters of Veterinary Science scholars as a primary advisor and worked as the co-advisor of twenty-five Masters scholars. He works in the fields of machine learning, data mining, forecasting, statistical modeling, and economic loss estimation due to livestock diseases. As an expert in these topics, he regularly delivers lectures to the scientists, faculty, and students in the field of statistical methods and applications.