Variance


### spurious Pattern Comes from randomness of dataset
Variance captures how the **random nature of the finite dataset** not family of model
i.e. the sensitivity of the model to the randomness in the dataset
$$Var(X) = E[(X - E[X])^2] \newline=  E[X^2] - 2E[X]E[X] + E[X]^2 \newline = E[X^2] - E[X]^2$$
$$Var(X) = Cov(X, X)$$
### Variance Usages
|Title|
|:-:|
|[ANOVA](https://texonom.com/anova-aad04dffd648401c8c44525003c6f083)|
|[law of total variance](https://texonom.com/law-of-total-variance-481cd44bdfde4e069f7f5f6913e17eb8)|








