Day 1 - Descriptive Statistics
Day 2 - Experiment design (Sampling Theorem, Normal Distribution, Confidence Intervals, Sample size determination, Propensity Matching)
Day 3 - Hypothesis Testing (Parametric and Nonparametric tests, Paired Tests)
Day 4 - Linear Regression, Logistic Regression
Day 5 - Anova and different applications
Day 6 - Principal Component Analysis and its applications in experimental design (Batch Effects, mislabelling, etc.)
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