# Introduction to Likelihood Theory

## Course description edit

The goal of this course is to familiarize students with the formal definition of likelihood and its properties relevant to statistics, with all the demonstrations and proofs included. Initially, there is no intention to go beyond maximum likelihood estimation and basic likelihood ratio tests. The prerequisites are a good course of probability theory, including probability spaces of arbitrary dimension, calculus in R^{n}, basic matrix algebra and a little experience with statistics and higher mathematics.

## Course news edit

**Monday, September 10, 2006**- Course open!

--Lucas Gallindo 17:21, 10 September 2006 (UTC)

## Learning materials and learning projects edit

- The Basic Definitions
- Maximum Likelihood Estimation
- Likelihood Ratio Tests
- The Case of The Exponential Family
- Profile Likelihood Confidence Intervals

### Wikipedia edit

### Wikibooks edit

Works in progress: b:Statistics <-- This book is considered a prerequisite.

## Active participants edit

The histories of Wikiversity pages indicate who the active participants are. If you are an active participant in this department, you can list your name here (this can help small departments grow and the participants communicate better; for large departments a list of active participants is not needed).