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It is well known that the foundation and development of statistical theory came up with a search for interpretation of results of research experiments, hence decision making, in biological, agricultural and medical fields. This endeavour gave birth to a new stream of mathematical sciences named statistics.

The present book aims to provide basic knowledge and explain application of biostatistics to master’s level students pursuing courses in different disciplines and also to help young researchers. This book effectively summarizes the author’s several years’ experience of teaching and research.

The author has also drawn ideas from her interaction with researchers in a variety of disciplines such as education, social science, life sciences, agricultural sciences, medical sciences, earth sciences and engineering.

The book covers almost all parts of the recent UGC model syllabus in biological sciences relating to quantitative zoology. It explains how to choose an appropriate statistical analysis method for various biological experimental data.

This book may be used as a textbook by undergraduate and postgraduate students of biostatistics in biological, agricultural and health sciences. It will help researchers in these and other aforesaid disciplines.

Contents: Preface. I. Basic: 1. Introduction. 2. Data Handling I: Graphical Methods. 3. Data Handling II: Descriptive Statistics. 4. Concepts of Probability. 5. Random Variables and their Characteristics. 6. Distributions. 7. Biostatistical Inference. 8. Tests of Significance. 9. Bivariate and Multivariate Data: Measuring and Testing Relationship. 10. Analysis of Categorical Data: Independence and Association. 11. Electronic Data Handling. Part II. Advanced: 12. Types and Architecture of Studies. 13. Data Collection: Census and Sampling. 14. Analysis of Data: With Violated Assumptions and from Complex Designs. 15. Non-Parametric Methods I: One Sample Tests. 16. Non-Parametric Methods II: Two Sample Tests. 17. Non-Parametric Methods III: k-Sample Tests. 18. Time Series Analysis. 19. Bioassay. 20. Multivariate Analysis I. 21. Multivariate Analysis II. 22. Bioinformatics and Computational Biology. 23. Computer Techniques. Appendices. References. Subject Index.