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.

• Credits: 3
• Faculty: Faculty of Engineering
• Department: Bioengineering
• Taught by: Jasmin Coulombe-Huntington

Sections offered

• Section 001 (Lec), Tue Thu 10:05-11:25 am — 3 seats open
• Section 002 (Tut), Fri 2:35-4:25 pm — 3 seats open