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Modern repeated measures analysis using mixed models in SPSS (1) Repeated measures analyse an introduction to the Mixed models (random effects) option in SPSS. Demonstrates different Covariance matrix types & how to use the Likelihood ratio test to evaluate different models. Robin Beaumont Full notes MCQ's etc at:

PCA w. prcomp: covariance or correlation matrix based results

Smaller is better for nanotube analysis

Generating the Variance-Covariance Matrix - YouTube


Inverse of a Matrix-2x2, real life example

Variance-covariance matrix using matrix notation of factor analysis - YouTube

Verification of the assumption of equal covariance matrices. eigenvalue decomposition performed for the covariance matrices of 2: target and nontarget. The eigenvectors (or principal components) corres. 4 largest eigenvalues visualized as scalp topographies ( scalearbitrary, max abs val 1. scale − 1 to 1 [arbitrary unit]). The similarity of the corresponding maps for the two classes can be seen as an indication that the covariance matrices of the two classes can be assumed to be equal.

To find the sample covariance matrix, should you divide by N or N-1 to get an unbiased estimate?

A Linear Algebra Primer for Financial Engineering: Covariance Matrices, Eigenvectors, OLS, and more (Financial Engineering Advanced Background Series)