Course Schedule

Syllabus

  • Introduction (5/1)   Descriptive statistics, data visualization

  • Random variables and probability distributions (5/3, 5/8)

  • Parameter estimation (5/10)

  • Hypothesis testing (5/15, 5/17, 5/22)

  • Regression methods (5/24)

  • Bootstrapping, cross validation and permutation tests (5/29)

  • Assessing significance in high dimensional experiments (5/31)

Homework assignments

  • Problem Set 1: Out 5/3. Due 5/10.

  • Problem Set 2: Out 5/10. Due 5/17.

  • Problem Set 3: Out 5/17. Due 5/22.

  • Problem Set 4: Out 5/22. Due 5/29.