设二维随机变量 (X , Y )服从二维正态分布,则随机变量X + Y与X – Y不相关的充要条件为( ) A: E (X ) = E (Y ) B: E (X 2) – [E (X )]2 = E (Y 2 ) – [E (Y )]2 C: E (X 2 ) = E (Y 2) D: E (X 2) + [E (X )]2 = E (Y 2 ) + [E (Y )]2
设二维随机变量 (X , Y )服从二维正态分布,则随机变量X + Y与X – Y不相关的充要条件为( ) A: E (X ) = E (Y ) B: E (X 2) – [E (X )]2 = E (Y 2 ) – [E (Y )]2 C: E (X 2 ) = E (Y 2) D: E (X 2) + [E (X )]2 = E (Y 2 ) + [E (Y )]2
设 (X, Y) 为二维随机变量,则随机变量ξ = X + Y 与η = X − Y 不相关的充分必要条件为() A: E(X<sup>2</sup>) −[E(X)]<sup>2</sup>= E(Y<sup>2</sup>) −[E(Y)]<sup>2</sup>; B: E(X<sup>2</sup>) = E(Y<sup>2</sup>); C: E(X) = E(Y); D: E(X<sup >2</sup>) + [E(X)]<sup >2</sup>= E(Y<sup >2</sup>) + [E(Y)]<sup >2</sup>.
设 (X, Y) 为二维随机变量,则随机变量ξ = X + Y 与η = X − Y 不相关的充分必要条件为() A: E(X<sup>2</sup>) −[E(X)]<sup>2</sup>= E(Y<sup>2</sup>) −[E(Y)]<sup>2</sup>; B: E(X<sup>2</sup>) = E(Y<sup>2</sup>); C: E(X) = E(Y); D: E(X<sup >2</sup>) + [E(X)]<sup >2</sup>= E(Y<sup >2</sup>) + [E(Y)]<sup >2</sup>.
设\(z = u{e^v}\),\(u = {x^2} + {y^2}\),\(v = xy\),则\( { { \partial z} \over {\partial x}}=\) A: \({e^{xy}}({x^2}y + {y^3} + 2x)\) B: \({e^{xy}}({x}y^2 + {y^3} + 2x)\) C: \({e^{xy}}({x}y + {y^3} + 2x)\) D: \({e^{xy}}({x^2}y + {y^2} + 2x)\)
设\(z = u{e^v}\),\(u = {x^2} + {y^2}\),\(v = xy\),则\( { { \partial z} \over {\partial x}}=\) A: \({e^{xy}}({x^2}y + {y^3} + 2x)\) B: \({e^{xy}}({x}y^2 + {y^3} + 2x)\) C: \({e^{xy}}({x}y + {y^3} + 2x)\) D: \({e^{xy}}({x^2}y + {y^2} + 2x)\)
方程$(x^2+1)(y^2-1) + xy y' = 0$的通解为 A: $y^2 = C \frac{e^{-x^2}}{x^2}$ B: $y = C \frac{e^{-x^2}}{x^2}$ C: $y^2 = C \frac{e^{-x^2}}{x^2}+1$ D: $y=C \frac{e^{-x^2}}{x^2}+1$
方程$(x^2+1)(y^2-1) + xy y' = 0$的通解为 A: $y^2 = C \frac{e^{-x^2}}{x^2}$ B: $y = C \frac{e^{-x^2}}{x^2}$ C: $y^2 = C \frac{e^{-x^2}}{x^2}+1$ D: $y=C \frac{e^{-x^2}}{x^2}+1$
求方程$y\frac{{{d}^{2}}y}{d{{x}^{2}}}-(\frac{dy}{dx})^{2}=0$的通解: A: $y={{C}_{1}}{{e}^{-{{C}_{2}}x}}$ B: $y={{C}_{1}}{{e}^{-{{C}_{2}}{{x}^{2}}}}$ C: $y={{C}_{1}}x{{e}^{-{{C}_{2}}{{x}^{2}}}}$ D: $y={{C}_{1}}{{e}^{{{C}_{2}}x}}$
求方程$y\frac{{{d}^{2}}y}{d{{x}^{2}}}-(\frac{dy}{dx})^{2}=0$的通解: A: $y={{C}_{1}}{{e}^{-{{C}_{2}}x}}$ B: $y={{C}_{1}}{{e}^{-{{C}_{2}}{{x}^{2}}}}$ C: $y={{C}_{1}}x{{e}^{-{{C}_{2}}{{x}^{2}}}}$ D: $y={{C}_{1}}{{e}^{{{C}_{2}}x}}$
已知E(X)=2,E(Y)=2,E(XY)=4,则X,Y 的协方差Cov(X,Y)= 。
已知E(X)=2,E(Y)=2,E(XY)=4,则X,Y 的协方差Cov(X,Y)= 。
下列函数中( )不是方程\( y' + xy = 0 \)的解。 A: \( y = {e^{ - { { {x^2}} \over 2}}} \) B: \( \ln \left| y \right| = - { { {x^2}} \over 2} \) C: \( y = {e^{ - { { {x^2}} \over 2}}} + 2 \) D: \( \ln \left| y \right| = - { { {x^2}} \over 2} +2\)
下列函数中( )不是方程\( y' + xy = 0 \)的解。 A: \( y = {e^{ - { { {x^2}} \over 2}}} \) B: \( \ln \left| y \right| = - { { {x^2}} \over 2} \) C: \( y = {e^{ - { { {x^2}} \over 2}}} + 2 \) D: \( \ln \left| y \right| = - { { {x^2}} \over 2} +2\)
设X,Y为随机变量,E(X)=E(Y)=1,Cov(X,Y)=2,则E(2XY)= A: -6 B: -2 C: 2 D: 6
设X,Y为随机变量,E(X)=E(Y)=1,Cov(X,Y)=2,则E(2XY)= A: -6 B: -2 C: 2 D: 6
设随机变量X与Y相互独立,E(X)=E(Y)=μ,D(X)=D(Y)=σ^2,则E(X-Y)^2=
设随机变量X与Y相互独立,E(X)=E(Y)=μ,D(X)=D(Y)=σ^2,则E(X-Y)^2=
已知y为二维数组,删除y的第2行的命令为( ) A: y(:,1:2)=[ ] B: y(2, C: =[ ] D: y(:, E: =[ ] F: y(:,2)=[ ]
已知y为二维数组,删除y的第2行的命令为( ) A: y(:,1:2)=[ ] B: y(2, C: =[ ] D: y(:, E: =[ ] F: y(:,2)=[ ]