Statistics

29 Episodes

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Regression vodcast 3.3

2013-10-1703:131

Further features of the hat matrix; y=Hy, X=HX, e=(I-H)y [Released under Creative Commons Attribution-NonCommercial-ShareAlike 2.0 UK: England & Wales licence.]

Regression vodcast 3.2

2013-10-1704:59

Properties of (I-H); symmetric, idempotent, trace = n-p [Released under Creative Commons Attribution-NonCommercial-ShareAlike 2.0 UK: England & Wales licence.]

Exponential.Family_the.Binomial

2013-02-1807:09

This video shows that the Binomial belongs to the Exponential Family. [Released under Creative Commons Attribution-NonCommercial-ShareAlike 2.0 UK: England & Wales licence.]

Binomial.Conjugate.Analysis

2013-02-1808:13

In this video Bayes' theorem is applied to the Binomial density, choosing an appropriate conjugate prior. [Released under Creative Commons Attribution-NonCommercial-ShareAlike 2.0 UK: England & Wales licence.]

GLMs - estimating phi

2013-01-1605:08

Brief slide explaining how to estimate phi in a GLM [Released under Creative Commons Attribution-NonCommercial-ShareAlike 2.0 UK: England & Wales licence.]

Normal Density (Canonical) Exponential Family Format

2013-01-16--:--

The Normal density written in (Canonical) form of the Exponential Family format suitable for GLMs [Released under Creative Commons Attribution-NonCommercial-ShareAlike 2.0 UK: England & Wales licence.]

Exponential family (canonical form)

2013-01-1105:40

Brief outline of the canonical form of the exponential family, illustrated with the Poisson distribution. [Released under Creative Commons Attribution-NonCommercial-ShareAlike 2.0 UK: England & Wales licence.]

Introduction to Standard Uniform Distribution

2013-01-1111:17

This briefly and roughly introduces the standard uniform distribution [Released under Creative Commons Attribution-NonCommercial-ShareAlike 2.0 UK: England & Wales licence.]

Regression: one possible model

2012-12-0806:24

Here we set out the simplest statistical model we could perhaps suggest for the regression situation, and see what beta_2 is in terms of moments [Released under Creative Commons Attribution-NonCommercial-ShareAlike 2.0 UK: England & Wales licence.]

Maximum_likelihood_mu_js

2012-11-0219:07

Maximum likelihood for the Normal distribution [Released under Creative Commons Attribution-NonCommercial-ShareAlike 2.0 UK: England & Wales licence.]

Regression as a projection problem

2012-10-1905:31

This attempts to sketch out regression as a problem for vec(y), vec(x1), vec(x2) etc. [Released under Creative Commons Attribution-NonCommercial-ShareAlike 2.0 UK: England & Wales licence.]

Hat matrix

2012-10-1913:06

A brief introduction to the hat matrix, and some ideas around leverage [Released under Creative Commons Attribution-NonCommercial-ShareAlike 2.0 UK: England & Wales licence.]

Revision of single variable least squares

2012-10-0804:29

Assumes we've done this in a previous course (linear algebra/calculus or even statistics) [Released under Creative Commons Attribution-NonCommercial-ShareAlike 2.0 UK: England & Wales licence.]

Regression-application to New York Restaurant Prices

2012-10-0228:04

We briefly outline the kind of work we intend to develop by examining a simple regression model fitted to the Zagat data on New York Restaurants. [Released under Creative Commons Attribution-NonCommercial-ShareAlike 2.0 UK: England & Wales licence.]

Poisson MGF

2012-09-2104:50

A description of the Moment Generating Function for the Poisson distribution, and one example of its use. [Released under Creative Commons Attribution-NonCommercial-ShareAlike 2.0 UK: England & Wales licence.]

The Poisson PMF

2012-09-2105:48

Brief explanation of the Poisson probability mass function (no explanation of where the formula comes from, but there is a check that it is a valid probability function and we find E[X]) [Released under Creative Commons Attribution-NonCommercial-ShareAlike 2.0 UK: England & Wales licence.]

Binomial

2012-09-1109:34

Description of the Binomial(n,p) distribution, find the first moment, state Var(X) [Released under Creative Commons Attribution-NonCommercial-ShareAlike 2.0 UK: England & Wales licence.]

Geometric Distribution

2012-09-1104:42

Some properties and derivation of the Geometric distribution, including check on validity and finding E[X] [Released under Creative Commons Attribution-NonCommercial-ShareAlike 2.0 UK: England & Wales licence.]

Binomial MLE

2012-09-1106:06

A brief description of how we obtain the Binomial m.l.e. [Released under Creative Commons Attribution-NonCommercial-ShareAlike 2.0 UK: England & Wales licence.]

Exponential MLE

2012-09-1103:32

Finds the maximum likelihood estimator for the exponential distribution [Released under Creative Commons Attribution-NonCommercial-ShareAlike 2.0 UK: England & Wales licence.]

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