Statistics Tutorials

Extending Expectation Propagation for Graphical Moby lee Luther

50 Pages |1867 Views

Extending Expectation Propagation for Graphical Models Yuan (Alan) Qi Joint work with Tom Minka Motivation Graphical models are widely used in...

6.041 / 6.431 7. Multiple Discrete Random Variablesby LearnOnline Through OCW

3 Pages |264 Views

In this lecture notes we are going to continue with Multiple Discrete Random Variables and This lesson described the following objectives:

•...

6.041/6.431 5.Discrete random variables; probability mass functionsby LearnOnline Through OCW

3 Pages |298 Views

This lesson described the following objectives:
1. Random variables
2. Probability Mass Function (PMF)
3. Expectation and
4. Variance...

6.041 / 6.431 18. Markov Chains - IIIby LearnOnline Through OCW

3 Pages |172 Views

In this lecture notes we are going to continue with Markov Chains - III. Review of steady-state behavior.This lecture explores Probability of blocked...

6.041 / 6.431 20. Central Limit Theoremby LearnOnline Through OCW

3 Pages |221 Views

This lecture notes introduces "THE CENTRAL LIMIT THEOREM".
CDF of Zn converges to normal CDF.Various topics covered under this section are Normal...

6.042J/18.062J 9. Partial Ordersby LearnOnline Through OCW

6 Pages |112 Views

This lecture notes introduces Partial Orders.Partial order is basically a binary relation over a set which is Reflexive, Antisymmetry and Transitieve...

6.041/6.431 17. Markov Chains - IIby LearnOnline Through OCW

3 Pages |118 Views

In this lecture notes we are going to continue with Markov Chains - II.
Mainly there are two topics discussed in this lecture notes:
...

6.041 / 6.431 3. Independence of Eventsby LearnOnline Through OCW

3 Pages |123 Views

This lecture notes introduces Independence of Two Events and Independence of a collection of events. If there are two events A and B occurrence of A ...

6.041 / 6.431 1. Probability Models and Axiomsby LearnOnline Through OCW

3 Pages |274 Views

This lecture notes introduces Probability Models and Axioms . Probability as a mathematical frame work for reasoning about uncertainty. Topics covered...

6.041 / 6.431 11. Derived Distributions; Convolution; Covarianceby LearnOnline Through OCW

3 Pages |225 Views

Upon completion of this lesson, you should be able to understand Derived distributions, convolution, covariance and correlation. Here, Correlation coe...