Week 1: Introduction to Biostatistics, applications of biostatistics, discussion of few use cases.
Week 2: Introduction to statistics, Need for statistics, Role of probability, Discussion of descriptive statistics
Week 3: Discussion of Mean, Median and mode, Introduction to probability theory, probability distributions, Expectations, Population variance, sample statistics, Inferential statistics
Week 4: Central limit theorem, Confidence intervals, Introduction to Hypothesis testing, Elements of Hypothesis testing, Large sample test, p-values
Week 5: Small sample test, T-distribution, Type I error, Type II error, Power of test, Chi-Square distribution, Hypothesis test using variance, Contingency test, Test of Independence, Probability plots
Week 6: Hypothesis test for two independent population, paired T test, F-distribution, Detailed discussion on ANOVA, Derivation of Mean Squared Treatment and Mean Squared Error in ANOVA, Sample problems
Week 7: Joint distribution, Covariance & Correlation between random variables, Simple Linear Regression, R-squared statistic, Confidence intervals for regression parameters, Multiple Linear Regression, Adjusted R-Squared statistic
Week 8: Logistic Regression, logit function, Derivation of log-likelihood function, Revisit ANOVA using linear regression, Derivation of ANOVA equations, Sample problems
Week 9: Introduction to Blocking, Randomized Complete Block Design, Latin square design, Sample Problems
Week 10: Graeco-Latin Square design, Introduction to factorial design, 22 factorial design, Discussion on interactions
Week 11: 23 factorial design, Derivation of relevant equations, Sample problems
Week 12: 2-Way ANOVA, Use cases, Derivations, Sample problems
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