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(2 classifications) (14 resources)

Probability -- Multivariate Distributions -- Expectations

Statistical Topic Classifications
Correlation (25)
Covariance (2)

Resources
View Resource Cartoon: Moments of a Random Variable

A cartoon to teach about finding the moments of a distribution. Cartoon by John Landers (www.landers.co.uk) based on an idea from Dennis Pearl (The Ohio State University). Free to use in the classroom and on course web sites.

http://www.causeweb.org/resources/fun/db.php?id=24
View Resource DAU StatRefresher Site Index Page

This is the subject and lesson listing for the DAU statistics refresher course. Topics include clustering algorithms, correlation coefficient, conditional probability, data analysis, eleven types of distributions, measures of central tendency, multiple regression, random variables, rank correlation, residual analysis, scatter plots, standard deviation, uniform distribution, and variance. They...

http://cs.gmu.edu/cne/modules/dau/stat_idx_frm.html
View Resource DAU StatRefresher: Clustering Algorithms

This interactive module helps students to understand the definition of and uses for clustering algorithms. Students will learn to categorize the types of clustering algorithms, to use the minimal spanning tree and the k-means clustering algorithm, and to solve exercise problems using clustering algorithms.

http://cs.gmu.edu/cne/modules/dau/stat/clustgalgs/clustgalgs...
View Resource DAU StatRefresher: Data Analysis

This is an interactive tutorial on Data Analysis topics including representations of data, understand the definition of mean, understand the definition of variance, recognize a few other useful concepts, recognize various sampling techniques, and solve exercise problems using data analysis.

http://cs.gmu.edu/cne/modules/dau/stat/data/data_frm.html
View Resource DAU StatRefresher: Expectations

This interactive tutorial on Expectations helps students understand the concept of expectations, recognize and use variance and standard deviation, understand the method of moments, recognize and use co-variance, and solve exercise problems using expectations.

http://cs.gmu.edu/cne/modules/dau/prob/expectations/expectat...
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