BIEN 203. Introduction to Statistics and Data Science

Probability, adding and multiplying probabilities, conditional and joint probabilities, variables, independence, confidence intervals, p- values and null models, central limit theorem, law of large numbers, statistical power, data normalization, pseudo-counts, T-tests, U test, ANOVA, Chi-squared test, Fisher’s exact test, Kolmogorov– Smirnov test, sampling/simulated null models, Monte Carlo methods, random walks, multiple-testing correction, data visualization, linear regression, clustering, dimensional reduction, data integration and classification. Analysis of large datasets, useand automation of functions from the Statsmodels and Matplotlib Python modules.