1. A method of modeling statistical variation of field effect transistors having fingers comprising: physically measuring characteristics of existing transistors; extracting a scaled simulation based on said characteristics of said existing transistors using a first model; physically measuring characteristics of existing pairs of matched transistors; extracting random dopant fluctuations from said characteristics of said existing pairs of matched transistors using a second model; creating synthetic single finger data using said scaled simulation and said dopant fluctuation and applying the following expressions: I 1 = sxI e x = 48 48 + 24 ⁢ βσ Vt 2 + 6 ⁢ β 2 ⁢ σ Vt 4 + β 3 ⁢ σ Vt 6 ⅆ 4 ⁢ I ⅆ V t 4 = β ⁢ ⅆ 2 ⁢ I ⅆ V t 2 ; ⅆ 6 ⁢ I ⅆ V t 6 = β 2 ⁢ ⅆ 2 ⁢ I ⅆ V t 2 ⁢ where ⁢ ⁢ = ⅆ 2 ⁢ I ⅆ V t 2 I and where d n represents a derivative level, I represents current, V t represents threshold voltage, and σ Vt n represents variance of threshold voltage; extracting a single finger model from said synthetic single finger data and said random dopant fluctuations using said first model; creating an ensemble model by applying the following expression: s = 1 - ( 2 n - 1 n 2 ) , where s comprises the skew between a typical single device model and a typical ensemble model, and n comprises the number of devices in the ensemble; and adjusting parameters of said first model to cause said single finger to match targets for said single finger.