Introduction to Likelihood Theory
Course description
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
- Monday, September 10, 2006 - Course open!
--Lucas Gallindo 17:21, 10 September 2006 (UTC)
Learning materials and learning projects
Wikiversity has adopted the "learning by doing" model for education. Lessons should center on learning activities for Wikiversity participants. Learning materials and learning projects can be used by multiple departments. Cooperate with other departments that use the same learning resource.
Learning materials and learning projects are located in the main Wikiversity namespace. Simply make a link to the name of the lesson (lessons are independent pages in the main namespace) and start writing!
- The Basic Definitions
- Maximum Likelihood Estimation
- Likelihood Ratio Tests
- The Case of The Exponential Family
- Profile Likelihood Confidence Intervals
Wikipedia
Wikibooks
Works in progress: b:Statistics <-- This book is considered a prerequisite.
Active participants
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).