均值/期望 x ˉ \bar{x} xˉ(mean):平均下来 方差 σ 2 \sigma^2 σ2(variance):数据的离散程度 σ x 2 = 1 n ∑ i = 1 n ( x i − x ˉ ) 2 \sigma^2_x=\dfrac{1}{n}\displaystyle\sum^n_{i=1}(x_i-\bar{x})^2 σx2=n1i=1∑n(xi−xˉ)2 协方差 c o v cov cov(covariance): c o v ( x , y ) = cov(x,y)= cov(x,y)= c o v ( X , Y ) = E ( X − E X ) ( Y − E Y ) cov(X, Y) = E(X-EX)(Y-EY) cov(X,Y)=E(X−EX)(Y−EY) c o v ( x , y ) = 1 n ∑ i = 1 n ( x i − x ˉ ) ( y i − y ˉ ) cov(x,y)=\dfrac{1}{n}\displaystyle\sum^n_{i=1}(x_i-\bar{x})(y_i-\bar{y}) cov(x,y)=n1i=1∑n(xi−xˉ)(yi−yˉ) c o v ( x , x ) = σ x 2 cov(x,x)=\sigma^2_{x} cov(x,x)=σx2 终于明白协方差的意义了