(New page: This is my little scratchpad for the variance. <math>Var(X) = E[(X-E[X])^2]</math> <math>Var(X) = E[(\sum_{i=1}{n} X_i - \sum_{i=1}{n}E[X_i])^2]</math> <math> = E[(\sum_{i=1}{n} (X_i - ...) |
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<math>Var(X) = E[(X-E[X])^2]</math> | <math>Var(X) = E[(X-E[X])^2]</math> | ||
| − | <math>Var(X) = E[(\sum_{i=1}{n} X_i - \sum_{i=1}{n}E[X_i])^2]</math> | + | <math>Var(X) = E[(\sum_{i=1}^{n} X_i - \sum_{i=1}^{n}E[X_i])^2]</math> |
| − | <math> = E[(\sum_{i=1}{n} (X_i - E[X_i]))^2]</math> | + | <math> = E[(\sum_{i=1}^{n} (X_i - E[X_i]))^2]</math> |
Still working on it. | Still working on it. | ||
Latest revision as of 10:13, 7 October 2008
This is my little scratchpad for the variance.
$ Var(X) = E[(X-E[X])^2] $
$ Var(X) = E[(\sum_{i=1}^{n} X_i - \sum_{i=1}^{n}E[X_i])^2] $
$ = E[(\sum_{i=1}^{n} (X_i - E[X_i]))^2] $
Still working on it.
