A Bayesian Perspective on Missing Data Imputation

Bayesian Generalized Linear Models

Penalized Linear Regression and Model Selection

Bayesian Linear Regression

Hierarchical Models

Metropolis-Hastings Algorithms

The Normal Model in a Two Parameter Setting

Bayesian Inference for the Normal Model

Monte Carlo Sampling

Bayesian Inference for the Poisson Model

Bayesian Inference for the Binomial Model

Frequentist Inference

Introduction to Bayesian Statistics

Eigenvalues and Eigenvectors

Spectral Analysis

Quadratic Form

Decomposition and Smoothing Methods

Projection Matrix

Matrix Trace

Model Fitting and Forecasting

ARMA Model

Moving Average Model

Autoregressive Series

Introduction

Linear Models

Likelihood Ratio Test

Optimal Tests

p-values

Statistical Decision

Statistical Test

Confidence Intervals

Optimal Unbiased Estimator

Sufficiency

Maximum Likelihood Estimator

The Method of Moments

Consistency

Bias and Variance

Brief Review Before STAT 6520

Sampling Distribution and Limit Theorems

Functions of Random Variables

Multivariate Probability Distributions

Common Continuous Random Variables

Definitions for Discrete Random Variables

Common Discrete Random Variables

Estimation

Conditional Probability

Basic Concepts

Definitions for Continuous Random Variables

Modern Nonparametric Regression

Categorical Data

Bootstrap

Density Estimation

Correlation and Concordance

Basic Tests for Three or More Samples

Two Independent Samples

Methods for Paired Samples

Other Single Sample Inferences

Location Inference for Single Samples

Basic Concepts

Fundamentals of Nonparametric Methods