#Statistics
2021
A Bayesian Perspective on Missing Data Imputation
Apr 26
Bayesian Generalized Linear Models
Apr 19
Penalized Linear Regression and Model Selection
Apr 12
Bayesian Linear Regression
Apr 05
Hierarchical Models
Mar 29
Metropolis-Hastings Algorithms
Mar 22
The Normal Model in a Two Parameter Setting
Mar 15
Bayesian Inference for the Normal Model
Feb 22
Monte Carlo Sampling
Feb 15
Bayesian Inference for the Poisson Model
Feb 08
Bayesian Inference for the Binomial Model
Jan 25
Frequentist Inference
Jan 18
Introduction to Bayesian Statistics
Jan 13
2020
Eigenvalues and Eigenvectors
Nov 18
Spectral Analysis
Nov 17
Quadratic Form
Nov 04
Decomposition and Smoothing Methods
Nov 02
Projection Matrix
Oct 23
Matrix Trace
Oct 07
Model Fitting and Forecasting
Sep 14
ARMA Model
Sep 12
Moving Average Model
Sep 04
Autoregressive Series
Aug 28
Introduction
Aug 28
Linear Models
Apr 21
Likelihood Ratio Test
Apr 18
Optimal Tests
Apr 14
p-values
Apr 09
Statistical Decision
Apr 01
Statistical Test
Apr 01
Confidence Intervals
Feb 08
Optimal Unbiased Estimator
Feb 02
Sufficiency
Jan 30
Maximum Likelihood Estimator
Jan 29
The Method of Moments
Jan 28
Consistency
Jan 27
Bias and Variance
Jan 25
Brief Review Before STAT 6520
Jan 08
2019
Sampling Distribution and Limit Theorems
Dec 28
Functions of Random Variables
Dec 08
Multivariate Probability Distributions
Nov 06
Common Continuous Random Variables
Nov 01
Definitions for Discrete Random Variables
Oct 06
Common Discrete Random Variables
Oct 06
Estimation
Sep 30
Conditional Probability
Sep 26
Basic Concepts
Sep 25
Definitions for Continuous Random Variables
Sep 25
Modern Nonparametric Regression
May 08
Categorical Data
May 06
Bootstrap
May 06
Density Estimation
May 06
Correlation and Concordance
May 05
Basic Tests for Three or More Samples
May 04
Two Independent Samples
May 02
Methods for Paired Samples
Apr 29
Other Single Sample Inferences
Apr 26
Location Inference for Single Samples
Mar 26
Basic Concepts
Jan 25
Fundamentals of Nonparametric Methods
Jan 25