MVA Multivariate Statistical Analysis

Lectures for Multivariate Statistical Analysis

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Course Content

13 courselets

	MVA - Boxplots, Histograms, Kernel Densities (video)	16 min
	MVA - Boxplots, Histograms, Kernel Densities (pdf)	2.34 M

	MVA - Scatterplots, Faces, Curves and PCPs (pdf)	30.52 M
	MVA - Scatterplots, Faces, Curves and PCPs (video)	9 min

	MVA Matrixes Eigenvectors Decompositions (video)	30 min
	MVA Matrixes Eigenvectors Decompositions (pdf)	1.87 M

	MVA Quadtratic Forms and Geometry (pdf)	1.43 M
	MVA Quadtratic Forms and Geometry (video)	36 min

	MVA - Covariance Correlation and Summary (video)	11 min
	MVA - Covariance Correlation and Summary (pdf)	4.54 M

	MVA - t-Tests, Linear Regression (pdf)	1.52 M
	MVA - t-Tests, Linear Regression (video)	8 min

	MVA - Multivariate Distrubutions 1 (pdf)	11.01 M
	MVA - Multivariate Distrubutions 1 (video)	41 min

	MVA - Multivariate Distrubutions 2 (video)	39 min
	MVA - Multivariate Distrubutions 2 (pdf)	11.01 M

	MVA - Multivariate Distrubutions 3 (pdf)	11.01 M
	MVA - Multivariate Distrubutions 3 (video)	32 min

	MVA - Variable Selection (pdf)	2.59 M
	MVA - Variable Selection (video)	6 min

	MVA - Decomposition of Data Matrices (pdf)	2.06 M
	MVA - Decomposition of Data Matrices (video)	10 min

	MVA Principal Components (pdf)	4.09 M
	MVA Principal Components (video)	15 min

	MVA - Canonical Correlation Analysis (video)	16 min
	MVA - Canonical Correlation Analysis (pdf)	2.06 M

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General Overview

Description

Lectures based on the book: Härdle & Simar: Multivariate Statistical Analysis. The course presents multivariate statistical analysis in a comprehensive way, including the most useful standard approaches to multi-dimensional data. It also features numerous examples and provides the underlying links to the sourcecodes in R, Python or SAS code, allowing readers to reproduce all computations.

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Yiting Liu

About the Instructor

Raul Bag

About the Instructor

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Raul Bag

About the Instructor

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MVA Multivariate Statistical Analysis

MVA Multivariate Statistical Analysis

Course Content

Requirements

General Overview

Description

Meet the instructors !