Statistics Graduate Students Bootcamp

Led by Prof. Tianxi Li

Lecture time: Aug 10 – Aug 21, M-F, 9:00am-12:00pm, 1:30pm – 4:00pm.

Format: synchronous lectures on Zoom. Videos will be recorded and posted on Collab for review. The first 30mins – 1 hour of each day will be Q&A and open discussion time. Piazza platform is also available for open discussions.



Week 1 (morning sessions for calculus; afternoon sessions for linear algebra):

  • · Basic calculus: limits, continuity, derivatives, integration, multivariate calculus
  • · Linear algebra: linear spaces, basis, projections, linear systems of equations
  • · Matrix algebra: matrix operations, decompositions, matrix derivatives, SVD


Week 2 (2 days for probability, 2 days for statistical inference and 1 day for numerical methods):

  • · Probability as a quick summary of STAT 3110: probability properties (including conditional), random variables (expected value and variance), common distribution functions (binomial, Poisson, normal, uniform, exponential, gamma)
  • · Introductory statistical inference as a quick summary of STAT 2120: estimation, MLEs, bias, MSE, sampling distributions, confidence intervals, hypothesis testing
  • · Numerical methods: round-off error, pseudo-random number generation, root-finding or basic optimization methods, matrix computation