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Variance and covariance

General additive models. Variance and covariance. Sums of squares. M contains the mean. The coefficient of correlation. We deal with samples. For a matrix X that contains several variables holds. The diagonal matrix S X contains the standard deviations as entries .

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There is a hypothesis about dependent and independent variables

Assumptions of linear regression. There is a hypothesis about dependent and independent variables The relation is supposed to be linear We have a hypothesis about the distribution of errors around the hypothesized regression line.

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293 views • 19 slides

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Variance and covariance

There is a hypothesis about dependent and independent variables