Curriculum

CSE 103. A Practical Introduction to Probability and Statistics

Combinatorics. Distributions over discrete and continuous domains. Conditional probability and Independence. Bayesian inference. Random variables, expectation, mean, variance and covariance. Binomial and Poisson distributions. Markov and Chebyshev’s inequalities. Central limit theorem. Hypothesis testing. Regression.

CSE 103 is not duplicate credit for ECE 109, Econ 120A, or Math 183.

Prerequisites:

  • Math 20A-B and (Math 184A or CSE 21 or Math 154);
  • Python, jupyter notebooks.

Plan of classes

  • Week 1 Introduction to probability and statistics
  • Week 2 Review of CSE21
    • topic 1: sets
    • topic 2 counting
    • topic 3 combinatorics
  • Week 3 probability introduction
  • Week 4 conditional probability
  • Week 5 random variables expectation and variance
  • Week 6 continuous distributions
  • Week 7 statistics parameter estimation and confidence interval
  • Week 8 hypothesis testing
  • Week 9 regression and PCA
  • Week 10 Review before final