A comprehensive textbook of biostatistics targeted at non-mathematicians at an advanced bachelor level and above.
The book sequentially covers basic mathematics topics essential for biologists, such as scientific methodology, levels of measurement, and explores more advanced concepts, including Bayes Theorem and Non-linear regression, thereby complying with the biostatistics syllabus of various universities as well as competitive examinations. This application oriented book focuses on the decision-making process during statistical tests and graphing, which test/graph to use, how much would be the minimum sample size, how to interpret the results, and so on. Authored by Prof. Felix Bast, whose course in UGC SWAYAM, "Biostatistics and Mathematical Biology" had been ranked the 7th best MOOC worldwide in 2020”.
Features –
• Concise yet comprehensive textbook on the fundamental concepts of statistics.
• Focused on choosing the correct statistical test and interpreting the results.
• Non-mathematical approach; suitable for biologists and medical students.
• Recommendations for various statistical tests and their variations.
About the Author –
Prof. Felix Bast is an award-winning Indian Science Communicator and a public educator working currently as a full Professor at Central University of Punjab, India. He is an expert panellist of International Science Council, an elected fellow of Linnean Society of London, and a member of IUCN, Geneva. He holds Ph.D. in Marine Biology from MEXT, Japan (alumnus of Monbukagakusho: MEXT Japanese Govt. international doctoral fellowship), and served as expedition scientist in Indian Antarctic Mission.
Content –
1. Introduction to Biostatistics and Mathematical Biology, 2. Types of Studies, 3. Levels of Measurements, 4. Summarizing Data: Tabular Presentation, 5. Summarizing Data: Graphical Presentation, 6. Charting with Excel, 7. Descriptive Statistics: Point Estimates, 8. Descriptive Statistics: Interval Estimates, 9. Error Bars, 10. Moments, Normality Tests and Outliers, 11. Concepts of Population, Sample and Confidence Intervals, 12. Statistical Hypothesis Testing, 13. Statistical Significance and P-Values, 14. Relationship between Confidence Intervals and Statistical Significance, 15. Statistical Power and Choosing the Right Sample Size, 16. t-distribution and Tests of Significance Based on t-distribution, 17. F-distribution and Tests of Significance Based on the F-distribution, 18. Post-Hoc Tests, 19. χ2-distribution and Tests of Significance Based on χ2-distribution, 20. Comparing Proportions, 21. Gaussian, Lognormal, Binomial and Poisson Distributions 22. Pearson’s Correlation, 23. Simple Linear Regression, 24. Non-linear Regression, Multiple Regression, and Logistic Regression, 25. Non-parametric Tests, 26. Permutations and Combinations, 27. Probability, 28. Likelihood and Bayes’ Theorem, 29. Key Concepts of Statistics and Statistical Pitfalls to Avoid
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