STATS 200B
Theoretical Statistics
Statistics · 4 units · Graduate courses (200-299)
Sufficiency, exponential families, least squares, maximum likelihood estimation, Bayesian estimation, Fisher information, Cramér/Rao inequality, Stein’s estimate, empirical Bayes, shrinkage and penalty, confidence intervals. Likelihood ratio test, p-value, false discovery, nonparametrics, semi-parametrics, model selection, dimension reduction.
S/U or letter grading.
Requisites
UCLA lists no requisites for this course.
Requires
Everything that has to come before this course, not just the courses named in the requisite above.
Nothing — this is an entry point.
Unlocks
What this course is a requisite for, and what those courses lead to in turn.
STATS 200B
- STATS 201CAdvanced Modeling and Inference
- STATS 203Large Sample Theory, Including Resampling
- BIOSTAT 276Inferential Techniques that Use Simulation
- STATS 210Computer Intensive Methods
- STATS 211Topics in Economics and Machine Learning
- COM SCI M262CCurrent Topics in Causal Modeling, Inference, and Reasoning
- STATS 213Synthetic Data Generation
- STATS C236Introduction to Bayesian Statistics
- BIOSTAT 279Optimal Design Theory and Application
- STATS 240Multivariate Analysis
- STATS C263Generative Data Science
11 courses list this as a requisite. The whole downstream is here — 11 courses over 1 level. Every course here opens its own tree.