Probability And Statistics

Expected Value and Variance:

E[X + Y] = E[X] + E[Y]

E[cX] = c * E[X] where c is a constant

E[XY] = E[X] * E[Y] where X and Y are independent variables

measuring the spread of data: mean absolute deviation and mean squared deviation

Var[X] = E[X^2] - (E[X]^2)

Var[kX] = k^2 * Var[X]

Var[X + Y] = Var[X] + Var[Y] where X and Y are independent variables

deriving the E[X] and Var[X] for the iid variables

Markov's Inequality

an equation for the population variance using the sample mean, and the sample size

Miscellaneous

regression coefficient of y on x