Special distributions for Quantitative R.V. Discrete R.V. { Binomial Geometric } Continuous. R.V. { Uniform Normal } PPF? CDF? E(X)?: Std(X)? P(X=K)=? P(X<=K)=? shape: Skewness? Continuous R.V. PDF is meaningless. 1) PDF of continuous RV the height of the curve of corresponding point. P(X=k)=0. 2) the prob. of any given X=k, P(X=k) is Zero. Binomial: (1) definition of X: number of trials that succeeded in n trials. Geometric: (1) definition of X: the order of first success in a series of trials. Binomial Setting difference: total number of trials n. E(X)=Σx_i p_i. Std(X) = sqrt(Σ(x_i-μ)^2 p_i). Binomial: E(X)=μx = np. Std(X) = σx = sqrt(np(1-p)). 当np>10丑n(1-p)>10时. ・当np<10且P>0. Geometric: E(X)=μx = 1/p. Std(X) = sqrt((1-p)/p^2). 永远. 当n(1-p)<10旦P→1时.