General materials: lecture notes all [.pdf] 

Probability theory review [.pdf], more comprehensive notes [.pdf] 

Introduction: notes [.pdf], numerical examples [.pdf]

Point estimation: notes [.pdf], numerical examples [.pdf]

Confidence intervals: notes [.pdf], numerical examples [.pdf]

Hypothesis testing: notes [.pdf], numerical examples [.pdf]

Linear regression: notes [.pdf], numerical examples [.pdf]

2024 Fall: syllabus [.pdf] (generated by bb), syllabus [.pdf]

General materials: lecture notes all [.pdf], 

Classical nonparametric methods [.pdf]: rank based tests

Nonparametric smoothing [.pdf]: regression and density estimation

Bayesian nonparametric methods [.pdf]: Gaussian process regression  

2025 Spring: syllabus [.pdf]

2026 Spring: syllabus [.pdf]

General materials: lecture notes all [.pdf], 

Basic Bayesian models [.pdf]: one-parameter, univariate and multivariate Normal, Gaussian linear regression 

Advanced Bayesian models [.pdf]: probit, logit, sparse priors, dynamic linear models

Posterior computation via Monte Carlo approximation [.pdf]: ordinary Monte Carlo, Markov chain Monte Carlo 

Posterior computation via analytic approximation [.pdf]: Laplace approximation, variational Bayes

2025 Fall: syllabus [.pdf]

General materials: lecture notes [.pdf], 

R code: the birthday problem [.r], 

stock selection by mean and variance [.pdf] [.r]  [.png] 

gambling systems[.pdf] [.r] 

blackjack [.pdf] [.r]

2022 Fall: syllabus [.pdf], practice final [.pdf], final exam [.pdf]  

Results of the experiment guessing 2/3 of the average [wiki]: [.png] 

2024 Winter: syllabus [.pdf], 

  Results of the Blotto game [wiki]: round 1 [.csv], round 2 [.csv]

Results of the experiment guessing 2/3 of the average [wiki]: [.png] 

General materials: lecture notes[.pdf], 

math quiz[.pdf], 

selected problems[.pdf] 

notability notes (~21MB): 2024 Spring [.pdf],  2024 Summer [.pdf] 

2022 Winter: syllabus[.pdf], practice final[.pdf], final exam[.pdf]  

2022 Spring: syllabus[.pdf], practice midterm[.pdf],  midterm exam[.pdf], final exam[.pdf]  

2023 Summer: syllabus[.pdf], midterm exam[.pdf], final exam[.pdf]  

2023 Fall: syllabus [.pdf], midterm exam 1[.pdf], practice midterm exam 2 [.pdf], midterm exam 2 [.pdf], final exam [.pdf]   

2024 Spring: syllabus [.pdf], midterm exam 1 [.pdf], midterm exam 2 [.pdf], final exam [.pdf]  

2024 Summer: syllabus [.pdf], midterm exam 1 [.pdf], midterm exam 2 [.pdf], final exam [.pdf]    

General materials: lecture notes [.pdf], 

math quiz [.pdf]  

R code: method of moments [.r], 

MLE [.r], MLE Asymptotic Normality & CI [.r], 

bootstrap [.r], 

p value [.r], 

Bayesian methods [.r], Gibbs sampler of the Gaussian Mixture Model [.r]   

2023 Winter: syllabus [.pdf], practice final [.pdf], final exam [.pdf]

 Data project: questions.pdf, (synthetic) data[.csv]

2023 Spring: syllabus [.pdf], final exam [.pdf], IC final exam [.pdf] 

 Data project: questions.pdf, Santa Cruz rainfall days data [.pdf] [website]  

Lecture notes: lecture-introduction [.pdf] [.html] 

lecture-graphics [.pdf] [.html]  

2024 Spring: syllabus [.pdf],  

2022 Spring 

2023 Spring, co-organize with Sangwon Hyun 

2023 Fall, co-organize with Sangwon Hyun