为什么计算出VarX 和VarY后，最后一步代入公式 不用开根号？

NO.PZ2015120604000064问题如下 Accorng to the above table, whis the correlation of X anY, given the joint probability table above?A.-0.98.B.0.16.C.0.98.A is correctCorr(X,Y)=Cov(X,Y)σxσyCorr(X,Y)=\fr{ Cov(X,Y) }{ { \sigma }_{ x }{ \sigma }_{ y } } Corr(X,Y)=σx​σy​Cov(X,Y)​,Cov(X,Y)=-4.8, stanrviations of X anY are 1.90 an2.58, calculatebefore,thus correlation of X anY is -0.98这道题不难理解 但是感觉写了半张纸 费了很多分钟。请问有没有简便方法 或者这种计算量是真题会有的吗。

NO.PZ2015120604000064 问题如下 Accorng to the above table, whis the correlation of X anY, given the joint probability table above? A.-0.98. B.0.16. C.0.98. A is correctCorr(X,Y)=Cov(X,Y)σxσyCorr(X,Y)=\fr{ Cov(X,Y) }{ { \sigma }_{ x }{ \sigma }_{ y } } Corr(X,Y)=σx​σy​Cov(X,Y)​,Cov(X,Y)=-4.8, stanrviations of X anY are 1.90 an2.58, calculatebefore,thus correlation of X anY is -0.98 如题，看了之前的解析，还是不知道X和Y 的标准差怎么求出来的，能不能仔细讲解一下

NO.PZ2015120604000064 问题如下 Accorng to the above table, whis the correlation of X anY, given the joint probability table above? A.-0.98. B.0.16. C.0.98. A is correctCorr(X,Y)=Cov(X,Y)σxσyCorr(X,Y)=\fr{ Cov(X,Y) }{ { \sigma }_{ x }{ \sigma }_{ y } } Corr(X,Y)=σx​σy​Cov(X,Y)​,Cov(X,Y)=-4.8, stanrviations of X anY are 1.90 an2.58, calculatebefore,thus correlation of X anY is -0.98 因为要求correlation，所以要分别求出公式里面的covariance和stanrviation分别求E(x)和E(y)，得出1和1.6求方差variance，然后开根号得出标准差stanrviation，-- 1.8974和2.5768求covariance: - 4.8把第二点的标准差和第三点的协方差带入correlation的公式求出结果

NO.PZ2015120604000064 问题如下 Accorng to the above table, whis the correlation of X anY, given the joint probability table above? A.-0.98. B.0.16. C.0.98. A is correctCorr(X,Y)=Cov(X,Y)σxσyCorr(X,Y)=\fr{ Cov(X,Y) }{ { \sigma }_{ x }{ \sigma }_{ y } } Corr(X,Y)=σx​σy​Cov(X,Y)​,Cov(X,Y)=-4.8, stanrviations of X anY are 1.90 an2.58, calculatebefore,thus correlation of X anY is -0.98 可以告诉一下公式吗