Linked from

The 63 pages that link to Variance, each with the reason it gives.

• Law of total varianceNarrower topic: The identity decomposes this overall measure of spread.

• Regression toward the meanRelated: Variation between measurements leaves room for an extreme result to be followed by a less extreme one.

• Karamata's inequalityRelated: Squared deviation is convex, so equal-mean vectors ordered by majorization have ordered sums of squares and variances.

• KurtosisCompared with: Variance measures overall squared spread; kurtosis measures a standardized fourth-power feature.

• Continuous uniform distributionRelated: The interval’s width determines spread, with variance equal to its squared width divided by twelve.

• De Moivre–Laplace theoremRelated: The binomial variance sets the scale of fluctuations used in the approximation.

• Kolmogorov's inequalityRelated: Independence makes the partial sum's total variance the bound's numerator.

• Kolmogorov's two-series theoremRelated: Summable variances bound the cumulative fluctuations around the means.

• Popoviciu's inequalityNarrower topic: The inequality places a sharp upper bound on this measure of spread.

• Precision (metrology)Related: It quantifies measurement dispersion in squared units and underlies standard deviation.

• Bienaymé's identityNarrower topic: The identity concerns how this measure behaves when random variables are added.

• Fluctuations and noiseRelated: It quantifies the magnitude of fluctuations around a typical value.

• Ibragimov–Iosifescu conjectureRelated: A central limit theorem for sums requires their variance growth to support a nondegenerate normalization.