š§ Difference between correlation and covariance matrices
Variance/Covariance To start off, the sample variance formula is:
$$s^2 = \frac{\sum_{i=1}^{n}(x_i - \overline{x})^2} {n - 1 }$$First of all, $x - \overline{x}$ is a deviation score (deviation from what? deviation from the mean). Summing the deviations will just get us zero so the deviations are squared and then added together. The numerator of this formula is then called the sum of squared deviations which is literally what it is. This is not yet what we refer to as the variance (s2). We have to divide this by nā
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1 which is the sample degrees of freedom.
Oct 26, 2018