卷 4 填空题 本题共5小题,每小题3分,满分15分
1 设
f ( x ) = 1 − x 1 + x f(x) = \frac{1 - x}{1 + x} f ( x ) = 1 + x 1 − x
,则
f ( n ) ( x ) = f^{(n)}(x) = f ( n ) ( x ) =
______.
【答案】
f ( n ) ( x ) = 2 ( − 1 ) n n ! ( 1 + x ) n + 1 ( n ≥ 1 ) f^{(n)}(x) = \frac{2 (-1)^n n!}{(1+x)^{n+1}} \quad (n \geq 1) f ( n ) ( x ) = ( 1 + x ) n + 1 2 ( − 1 ) n n ! ( n ≥ 1 ) 【解析】
考虑函数
f ( x ) = 1 − x 1 + x f(x) = \frac{1-x}{1+x} f ( x ) = 1 + x 1 − x
。将其改写为
f ( x ) = 2 1 + x − 1 f(x) = \frac{2}{1+x} - 1 f ( x ) = 1 + x 2 − 1
。由于常数的导数为零,对于
n ≥ 1 n \geq 1 n ≥ 1
,有
f ( n ) ( x ) = ( 2 1 + x ) ( n ) f^{(n)}(x) = \left( \frac{2}{1+x} \right)^{(n)} f ( n ) ( x ) = ( 1 + x 2 ) ( n )
。 令
g ( x ) = 2 1 + x = 2 ( 1 + x ) − 1 g(x) = \frac{2}{1+x} = 2(1+x)^{-1} g ( x ) = 1 + x 2 = 2 ( 1 + x ) − 1
,则其
n n n
阶导数为:
g ( n ) ( x ) = 2 ⋅ ( − 1 ) n n ! ( 1 + x ) − n − 1 = 2 ( − 1 ) n n ! ( 1 + x ) n + 1 . g^{(n)}(x) = 2 \cdot (-1)^n n! (1+x)^{-n-1} = \frac{2 (-1)^n n!}{(1+x)^{n+1}}. g ( n ) ( x ) = 2 ⋅ ( − 1 ) n n ! ( 1 + x ) − n − 1 = ( 1 + x ) n + 1 2 ( − 1 ) n n ! . 因此,对于
n ≥ 1 n \geq 1 n ≥ 1
,
f ( n ) ( x ) = 2 ( − 1 ) n n ! ( 1 + x ) n + 1 . f^{(n)}(x) = \frac{2 (-1)^n n!}{(1+x)^{n+1}}. f ( n ) ( x ) = ( 1 + x ) n + 1 2 ( − 1 ) n n ! . 该公式已验证于
n = 1 , 2 , 3 , … n = 1, 2, 3, \ldots n = 1 , 2 , 3 , …
时成立。
2 设
z = x y f ( y x ) z = xyf\left(\frac{y}{x} \right) z = x y f ( x y )
,
f ( u ) f(u) f ( u )
可导,则
x z x ′ + y z y ′ = xz'_x + yz'_y = x z x ′ + y z y ′ =
______.
【答案】 2 z 2z 2 z
【解析】 给定
z = x y f ( y x ) z = xy f\left( \frac{y}{x} \right) z = x y f ( x y )
,其中
f ( u ) f(u) f ( u )
可导。 首先,计算偏导数
z x ′ z'_x z x ′
和
z y ′ z'_y z y ′
。 设
u = y x u = \frac{y}{x} u = x y
,则
z = x y f ( u ) z = xy f(u) z = x y f ( u )
。 求
z x ′ z'_x z x ′
:
z x ′ = ∂ ∂ x [ x y f ( u ) ] = y f ( u ) + x y ∂ f ( u ) ∂ x = y f ( u ) + x y f ′ ( u ) ∂ u ∂ x z'_x = \frac{\partial}{\partial x} [xy f(u)] = y f(u) + xy \frac{\partial f(u)}{\partial x} = y f(u) + xy f'(u) \frac{\partial u}{\partial x} z x ′ = ∂ x ∂ [ x y f ( u )] = y f ( u ) + x y ∂ x ∂ f ( u ) = y f ( u ) + x y f ′ ( u ) ∂ x ∂ u 其中
∂ u ∂ x = − y x 2 \frac{\partial u}{\partial x} = -\frac{y}{x^2} ∂ x ∂ u = − x 2 y
,所以
z x ′ = y f ( u ) + x y f ′ ( u ) ( − y x 2 ) = y f ( u ) − y 2 x f ′ ( u ) z'_x = y f(u) + xy f'(u) \left( -\frac{y}{x^2} \right) = y f(u) - \frac{y^2}{x} f'(u) z x ′ = y f ( u ) + x y f ′ ( u ) ( − x 2 y ) = y f ( u ) − x y 2 f ′ ( u ) 求
z y ′ z'_y z y ′
:
z y ′ = ∂ ∂ y [ x y f ( u ) ] = x f ( u ) + x y ∂ f ( u ) ∂ y = x f ( u ) + x y f ′ ( u ) ∂ u ∂ y z'_y = \frac{\partial}{\partial y} [xy f(u)] = x f(u) + xy \frac{\partial f(u)}{\partial y} = x f(u) + xy f'(u) \frac{\partial u}{\partial y} z y ′ = ∂ y ∂ [ x y f ( u )] = x f ( u ) + x y ∂ y ∂ f ( u ) = x f ( u ) + x y f ′ ( u ) ∂ y ∂ u 其中
∂ u ∂ y = 1 x \frac{\partial u}{\partial y} = \frac{1}{x} ∂ y ∂ u = x 1
,所以
z y ′ = x f ( u ) + x y f ′ ( u ) ⋅ 1 x = x f ( u ) + y f ′ ( u ) z'_y = x f(u) + xy f'(u) \cdot \frac{1}{x} = x f(u) + y f'(u) z y ′ = x f ( u ) + x y f ′ ( u ) ⋅ x 1 = x f ( u ) + y f ′ ( u ) 现在计算
x z x ′ + y z y ′ x z'_x + y z'_y x z x ′ + y z y ′
:
x z x ′ = x ( y f ( u ) − y 2 x f ′ ( u ) ) = x y f ( u ) − y 2 f ′ ( u ) x z'_x = x \left( y f(u) - \frac{y^2}{x} f'(u) \right) = xy f(u) - y^2 f'(u) x z x ′ = x ( y f ( u ) − x y 2 f ′ ( u ) ) = x y f ( u ) − y 2 f ′ ( u )
y z y ′ = y ( x f ( u ) + y f ′ ( u ) ) = x y f ( u ) + y 2 f ′ ( u ) y z'_y = y \left( x f(u) + y f'(u) \right) = xy f(u) + y^2 f'(u) y z y ′ = y ( x f ( u ) + y f ′ ( u ) ) = x y f ( u ) + y 2 f ′ ( u ) 相加得:
x z x ′ + y z y ′ = [ x y f ( u ) − y 2 f ′ ( u ) ] + [ x y f ( u ) + y 2 f ′ ( u ) ] = 2 x y f ( u ) x z'_x + y z'_y = [xy f(u) - y^2 f'(u)] + [xy f(u) + y^2 f'(u)] = 2xy f(u) x z x ′ + y z y ′ = [ x y f ( u ) − y 2 f ′ ( u )] + [ x y f ( u ) + y 2 f ′ ( u )] = 2 x y f ( u ) 由于
z = x y f ( u ) z = xy f(u) z = x y f ( u )
,所以
x z x ′ + y z y ′ = 2 z x z'_x + y z'_y = 2z x z x ′ + y z y ′ = 2 z 因此,答案为
2 z 2z 2 z
。
3 设
f ′ ( ln x ) = 1 + x f'(\ln x) = 1 + x f ′ ( ln x ) = 1 + x
,则
f ( x ) = f(x) = f ( x ) =
______.
【答案】 f ( x ) = x + e x + C f(x) = x + e^x + C f ( x ) = x + e x + C
,其中
C C C
为任意常数。
【解析】 给定
f ′ ( ln x ) = 1 + x f'(\ln x) = 1 + x f ′ ( ln x ) = 1 + x
,令
u = ln x u = \ln x u = ln x
,则
x = e u x = e^u x = e u
,代入得
f ′ ( u ) = 1 + e u f'(u) = 1 + e^u f ′ ( u ) = 1 + e u
。 对
f ′ ( u ) f'(u) f ′ ( u )
积分得
f ( u ) = ∫ ( 1 + e u ) d u = u + e u + C f(u) = \int (1 + e^u) \, du = u + e^u + C f ( u ) = ∫ ( 1 + e u ) d u = u + e u + C
,其中
C C C
为积分常数。 将
u u u
替换为
x x x
,得
f ( x ) = x + e x + C f(x) = x + e^x + C f ( x ) = x + e x + C
。 验证:若
f ( x ) = x + e x + C f(x) = x + e^x + C f ( x ) = x + e x + C
,则
f ′ ( x ) = 1 + e x f'(x) = 1 + e^x f ′ ( x ) = 1 + e x
,故
f ′ ( ln x ) = 1 + e ln x = 1 + x f'(\ln x) = 1 + e^{\ln x} = 1 + x f ′ ( ln x ) = 1 + e l n x = 1 + x
,符合原条件。
4 设
A = ( 1 0 0 2 2 0 3 4 5 ) A = \begin{pmatrix}
1 & 0 & 0 \\
2 & 2 & 0 \\
3 & 4 & 5
\end{pmatrix} A = 1 2 3 0 2 4 0 0 5
,
A ∗ A^* A ∗
是
A A A
的伴随矩阵,则
( A ∗ ) − 1 = (A^*)^{-1} = ( A ∗ ) − 1 =
______.
【答案】
1 10 ( 1 0 0 2 2 0 3 4 5 ) \frac{1}{10} \begin{pmatrix} 1 & 0 & 0 \\ 2 & 2 & 0 \\ 3 & 4 & 5 \end{pmatrix} 10 1 1 2 3 0 2 4 0 0 5 【解析】 由伴随矩阵的性质,有
A A ∗ = A ∗ A = det ( A ) I A A^* = A^* A = \det(A) I A A ∗ = A ∗ A = det ( A ) I
,其中
I I I
是单位矩阵。因此,
A ∗ = det ( A ) A − 1 A^* = \det(A) A^{-1} A ∗ = det ( A ) A − 1
,进而可得
( A ∗ ) − 1 = 1 det ( A ) A (A^*)^{-1} = \frac{1}{\det(A)} A ( A ∗ ) − 1 = d e t ( A ) 1 A
。 计算矩阵
A A A
的行列式:
A = ( 1 0 0 2 2 0 3 4 5 ) A = \begin{pmatrix} 1 & 0 & 0 \\ 2 & 2 & 0 \\ 3 & 4 & 5 \end{pmatrix} A = 1 2 3 0 2 4 0 0 5 由于
A A A
是下三角矩阵,行列式为对角元素的乘积,即
det ( A ) = 1 × 2 × 5 = 10 \det(A) = 1 \times 2 \times 5 = 10 det ( A ) = 1 × 2 × 5 = 10 因此,
( A ∗ ) − 1 = 1 10 A = 1 10 ( 1 0 0 2 2 0 3 4 5 ) (A^*)^{-1} = \frac{1}{10} A = \frac{1}{10} \begin{pmatrix} 1 & 0 & 0 \\ 2 & 2 & 0 \\ 3 & 4 & 5 \end{pmatrix} ( A ∗ ) − 1 = 10 1 A = 10 1 1 2 3 0 2 4 0 0 5 5 设
X 1 , X 2 , ⋯ , X n X_1,X_2, \cdots ,X_n X 1 , X 2 , ⋯ , X n
是来自正态总体
N ( μ , σ 2 ) N(\mu ,\sigma^2) N ( μ , σ 2 )
的简单随机样本,其中参数
μ \mu μ
和
σ 2 \sigma^2 σ 2
未知,
记
X ‾ = 1 n ∑ i = 1 n X i \overline{X}= \frac{1}{n}\sum_{i = 1}^n X_i^{} X = n 1 ∑ i = 1 n X i
,
Q 2 = ∑ i = 1 n ( X i − X ‾ ) 2 Q^2 = \sum_{i = 1}^n (X_i^{} - \overline{X})^2 Q 2 = ∑ i = 1 n ( X i − X ) 2
,
则假设
H 0 : μ = 0 H_0:\mu = 0 H 0 : μ = 0
的
t t t
检验使用统计量
t = t = t =
______.
【答案】
t = X ‾ n Q 2 n − 1 t = \frac{\overline{X} \sqrt{n}}{\sqrt{\frac{Q^2}{n-1}}} t = n − 1 Q 2 X n 【解析】
在假设检验中,当总体方差未知时,对总体均值进行t检验使用的统计量为
t = X ‾ − μ 0 s / n t = \frac{\overline{X} - \mu_0}{s / \sqrt{n}} t = s / n X − μ 0
,其中
μ 0 \mu_0 μ 0
为假设的总体均值,本题中
μ 0 = 0 \mu_0 = 0 μ 0 = 0
,
s s s
为样本标准差。样本方差
s 2 = 1 n − 1 ∑ i = 1 n ( X i − X ‾ ) 2 = Q 2 n − 1 s^2 = \frac{1}{n-1} \sum_{i=1}^n (X_i - \overline{X})^2 = \frac{Q^2}{n-1} s 2 = n − 1 1 ∑ i = 1 n ( X i − X ) 2 = n − 1 Q 2
,因此
s = Q 2 n − 1 s = \sqrt{\frac{Q^2}{n-1}} s = n − 1 Q 2
。代入t统计量公式,得到
t = X ‾ − 0 Q 2 n − 1 / n = X ‾ n Q 2 n − 1 t = \frac{\overline{X} - 0}{\sqrt{\frac{Q^2}{n-1}} / \sqrt{n}} = \frac{\overline{X} \sqrt{n}}{\sqrt{\frac{Q^2}{n-1}}} t = n − 1 Q 2 / n X − 0 = n − 1 Q 2 X n
。该统计量服从自由度为
n − 1 n-1 n − 1
的t分布,用于检验假设
H 0 : μ = 0 H_0: \mu = 0 H 0 : μ = 0
。
选择题 本题共5小题,每小题3分,满分15分
6 设
f ( x ) f(x) f ( x )
为可导函数,且满足条件
lim x → 0 f ( 1 ) − f ( 1 − x ) 2 x = − 1 \lim_{x \to 0} \frac{f(1) - f(1 - x)}{2x} = - 1 lim x → 0 2 x f ( 1 ) − f ( 1 − x ) = − 1
,
则曲线
y = f ( x ) y = f(x) y = f ( x )
在点
( 1 , f ( 1 ) ) (1,f(1)) ( 1 , f ( 1 ))
处的切线斜率为
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正确答案:D 【解析】 给定条件
lim x → 0 f ( 1 ) − f ( 1 − x ) 2 x = − 1 \lim_{x \to 0} \frac{f(1) - f(1 - x)}{2x} = -1 lim x → 0 2 x f ( 1 ) − f ( 1 − x ) = − 1
。令
h = − x h = -x h = − x
,则当
x → 0 x \to 0 x → 0
时,
h → 0 h \to 0 h → 0
,于是有:
f ( 1 ) − f ( 1 − x ) 2 x = f ( 1 ) − f ( 1 + h ) 2 ( − h ) = − [ f ( 1 + h ) − f ( 1 ) ] − 2 h = f ( 1 + h ) − f ( 1 ) 2 h . \frac{f(1) - f(1 - x)}{2x} = \frac{f(1) - f(1 + h)}{2(-h)} = \frac{-[f(1 + h) - f(1)]}{-2h} = \frac{f(1 + h) - f(1)}{2h}. 2 x f ( 1 ) − f ( 1 − x ) = 2 ( − h ) f ( 1 ) − f ( 1 + h ) = − 2 h − [ f ( 1 + h ) − f ( 1 )] = 2 h f ( 1 + h ) − f ( 1 ) . 因此,
lim h → 0 f ( 1 + h ) − f ( 1 ) 2 h = − 1. \lim_{h \to 0} \frac{f(1 + h) - f(1)}{2h} = -1. h → 0 lim 2 h f ( 1 + h ) − f ( 1 ) = − 1. 根据导数的定义,
f ′ ( 1 ) = lim h → 0 f ( 1 + h ) − f ( 1 ) h f'(1) = \lim_{h \to 0} \frac{f(1 + h) - f(1)}{h} f ′ ( 1 ) = lim h → 0 h f ( 1 + h ) − f ( 1 )
,所以:
1 2 f ′ ( 1 ) = − 1 , \frac{1}{2} f'(1) = -1, 2 1 f ′ ( 1 ) = − 1 , 解得
f ′ ( 1 ) = − 2 f'(1) = -2 f ′ ( 1 ) = − 2
。因此,曲线
y = f ( x ) y = f(x) y = f ( x )
在点
( 1 , f ( 1 ) ) (1, f(1)) ( 1 , f ( 1 ))
处的切线斜率为
− 2 -2 − 2
。
7 下列广义积分发散的是
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正确答案:A 【解析】 对于选项A,积分
∫ − 1 1 1 sin x d x \int_{-1}^1 \frac{1}{\sin x} dx ∫ − 1 1 s i n x 1 d x
在
x = 0 x=0 x = 0
处有奇点,因为
sin 0 = 0 \sin 0 = 0 sin 0 = 0
。当
x → 0 x \to 0 x → 0
时,
sin x ∼ x \sin x \sim x sin x ∼ x
,因此
1 sin x ∼ 1 x \frac{1}{\sin x} \sim \frac{1}{x} s i n x 1 ∼ x 1
,而积分
∫ 1 x d x \int \frac{1}{x} dx ∫ x 1 d x
在0附近发散,故该积分发散。
对于选项B,积分
∫ − 1 1 1 1 − x 2 d x \int_{-1}^1 \frac{1}{\sqrt{1 - x^2}} dx ∫ − 1 1 1 − x 2 1 d x
是标准积分,结果为
arcsin x ∣ − 1 1 = π 2 − ( − π 2 ) = π \arcsin x \big|_{-1}^1 = \frac{\pi}{2} - (-\frac{\pi}{2}) = \pi arcsin x − 1 1 = 2 π − ( − 2 π ) = π
,收敛。
对于选项C,积分
∫ 0 + ∞ e − x 2 d x \int_0^{+\infty} e^{-x^2} dx ∫ 0 + ∞ e − x 2 d x
是高斯积分,收敛于
π 2 \frac{\sqrt{\pi}}{2} 2 π
。
对于选项D,积分
∫ 2 + ∞ 1 x ln 2 x d x \int_2^{+\infty} \frac{1}{x \ln^2 x} dx ∫ 2 + ∞ x l n 2 x 1 d x
,令
u = ln x u = \ln x u = ln x
,则
d u = d x x du = \frac{dx}{x} d u = x d x
,积分变为
∫ ln 2 + ∞ 1 u 2 d u = − 1 u ∣ ln 2 + ∞ = 1 ln 2 \int_{\ln 2}^{+\infty} \frac{1}{u^2} du = -\frac{1}{u} \big|_{\ln 2}^{+\infty} = \frac{1}{\ln 2} ∫ l n 2 + ∞ u 2 1 d u = − u 1 l n 2 + ∞ = l n 2 1
,收敛。
因此,只有选项A发散。
8 设矩阵
A m × n A_{m \times n} A m × n
的秩为
r ( A ) = m < n r(A) = m < n r ( A ) = m < n
,
E m E_m E m
为
m m m
阶单位矩阵,下述结论中正确的是
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正确答案:C 【解析】 由于矩阵
A m × n A_{m \times n} A m × n
的秩
r ( A ) = m < n r(A) = m < n r ( A ) = m < n
,即
A A A
行满秩,因此行向量线性无关。左零空间(满足
x T A = 0 x^T A = 0 x T A = 0
的向量
x x x
的集合)仅包含零向量。若矩阵
B B B
满足
B A = 0 BA = 0 B A = 0
,则
B B B
的每一行向量均属于左零空间,故
B B B
的每一行为零向量,即
B = 0 B = 0 B = 0
,因此选项 C 正确。
选项 A 错误,因为秩为
m m m
仅保证存在
m m m
个线性无关的行向量,但并非任意
m m m
个行向量都线性无关。
选项 B 错误,因为秩为
m m m
仅保证至少有一个
m m m
阶子式非零,但并非任意
m m m
阶子式都不为零。
选项 D 错误,因为通过初等行变换,
A A A
可化为行最简形式
[ I m ∣ F ] [I_m \mid F] [ I m ∣ F ]
(其中
F F F
为
m × ( n − m ) m \times (n-m) m × ( n − m )
矩阵),但不一定能化为
( E m , 0 ) (E_m, 0) ( E m , 0 )
的形式,除非
F F F
为零矩阵。
9 设随机变量
X X X
和
Y Y Y
独立同分布,记
U = X − Y , V = X + Y U = X - Y,V = X + Y U = X − Y , V = X + Y
,则随机变量
U U U
与
V V V
必然
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正确答案:D 【解析】 设
E [ X ] = E [ Y ] = μ E[X] = E[Y] = \mu E [ X ] = E [ Y ] = μ
,
Var ( X ) = Var ( Y ) = σ 2 \text{Var}(X) = \text{Var}(Y) = \sigma^2 Var ( X ) = Var ( Y ) = σ 2
,且
X X X
与
Y Y Y
独立,故
Cov ( X , Y ) = 0 \text{Cov}(X, Y) = 0 Cov ( X , Y ) = 0
。 计算
U = X − Y U = X - Y U = X − Y
与
V = X + Y V = X + Y V = X + Y
的协方差:
Cov ( U , V ) = Cov ( X − Y , X + Y ) = Cov ( X , X ) + Cov ( X , Y ) − Cov ( Y , X ) − Cov ( Y , Y ) = Var ( X ) − Var ( Y ) = σ 2 − σ 2 = 0.
\begin{aligned}
\text{Cov}(U, V) &= \text{Cov}(X - Y, X + Y) \\
&= \text{Cov}(X, X) + \text{Cov}(X, Y) - \text{Cov}(Y, X) - \text{Cov}(Y, Y) \\
&= \text{Var}(X) - \text{Var}(Y) \\
&= \sigma^2 - \sigma^2 = 0.
\end{aligned}
Cov ( U , V ) = Cov ( X − Y , X + Y ) = Cov ( X , X ) + Cov ( X , Y ) − Cov ( Y , X ) − Cov ( Y , Y ) = Var ( X ) − Var ( Y ) = σ 2 − σ 2 = 0. 因此,
U U U
与
V V V
的相关系数为零。 注意:相关系数为零不一定意味着独立,例如当
X , Y X, Y X , Y
为伯努利分布时,
U U U
与
V V V
不独立。 本题中必然成立的结论是 相关系数为零 。
10 设随机变量
X X X
服从正态分布
N ( μ , σ 2 ) N(\mu,\sigma^2) N ( μ , σ 2 )
,则随
σ \sigma σ
的增大,
概率
P { ∣ X − μ ∣ < σ } P\left\{\left| X - \mu \right| < \sigma \right\} P { ∣ X − μ ∣ < σ }
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正确答案:C 【解析】 已知
X ∼ N ( μ , σ 2 ) X \sim N(\mu, \sigma^2) X ∼ N ( μ , σ 2 )
,令
Z = X − μ σ Z = \frac{X - \mu}{\sigma} Z = σ X − μ
,则
Z ∼ N ( 0 , 1 ) Z \sim N(0,1) Z ∼ N ( 0 , 1 )
。 于是
P { ∣ X − μ ∣ < σ } = P { ∣ Z ∣ < 1 } ≈ 0.6827
P\{|X - \mu| < \sigma\} = P\{|Z| < 1\} \approx 0.6827
P { ∣ X − μ ∣ < σ } = P { ∣ Z ∣ < 1 } ≈ 0.6827 该概率为常数,与
σ \sigma σ
无关,因此不随
σ \sigma σ
增大而改变。
解答题 11 设
f ( x ) = { 2 x 2 ( 1 − cos x ) , x < 0 1 , x = 0 1 x ∫ 0 x cos t 2 d t , x > 0 f(x) = \begin{cases}
\frac{2}{x^2}(1 - \cos x), & x < 0 \\
1, & x = 0 \\
\frac{1}{x}\int_0^x \cos t^2 \dt , & x > 0
\end{cases} f ( x ) = ⎩ ⎨ ⎧ x 2 2 ( 1 − cos x ) , 1 , x 1 ∫ 0 x cos t 2 d t , x < 0 x = 0 x > 0
,试讨论
f ( x ) f(x) f ( x )
在
x = 0 x = 0 x = 0
处的连续性和可导性.
【答案】 在
x = 0 x = 0 x = 0
处,
f ( x ) f(x) f ( x )
连续且可导。
【解析】 (Ⅰ) 先看左极限与右极限:
lim x → 0 − f ( x ) = lim x → 0 − 2 ( 1 − cos x ) x 2 = lim x → 0 − 2 ⋅ 1 2 x 2 x 2 = 1 , \lim_{x \to 0^-} f(x) = \lim_{x \to 0^-} \frac{2(1 - \cos x)}{x^2} = \lim_{x \to 0^-} \frac{2 \cdot \frac{1}{2}x^2}{x^2} = 1, x → 0 − lim f ( x ) = x → 0 − lim x 2 2 ( 1 − cos x ) = x → 0 − lim x 2 2 ⋅ 2 1 x 2 = 1 , lim x → 0 + f ( x ) = lim x → 0 + ∫ 0 x cos t 2 d t x = lim x → 0 + cos x 2 1 = 1. \lim_{x \to 0^+} f(x) = \lim_{x \to 0^+} \int_0^x \frac{\cos t^2 dt}{x} = \lim_{x \to 0^+} \frac{\cos x^2}{1} = 1. x → 0 + lim f ( x ) = x → 0 + lim ∫ 0 x x cos t 2 d t = x → 0 + lim 1 cos x 2 = 1. 故
f ( 0 + ) = f ( 0 − ) = f ( 0 ) f(0^+) = f(0^-) = f(0) f ( 0 + ) = f ( 0 − ) = f ( 0 )
,即
f ( x ) f(x) f ( x )
在
x = 0 x = 0 x = 0
处连续。
(Ⅱ) 再看左导数与右导数:
f + ′ ( 0 ) = lim x → 0 + f ( x ) − f ( 0 ) x − 0 = lim x → 0 + 1 x ∫ 0 x cos t 2 d t − 1 x f'_+(0) = \lim_{x \to 0^+} \frac{f(x) - f(0)}{x - 0} = \lim_{x \to 0^+} \frac{\frac{1}{x} \int_0^x \cos t^2 dt - 1}{x} f + ′ ( 0 ) = x → 0 + lim x − 0 f ( x ) − f ( 0 ) = x → 0 + lim x x 1 ∫ 0 x cos t 2 d t − 1 = lim x → 0 + ∫ 0 x cos t 2 d t − x x 2 = lim x → 0 + cos x 2 − 1 2 x = lim x → 0 + − 1 2 x 4 2 x = 0 , = \lim_{x \to 0^+} \int_0^x \frac{\cos t^2 dt - x}{x^2} = \lim_{x \to 0^+} \frac{\cos x^2 - 1}{2x} = \lim_{x \to 0^+} \frac{- \frac{1}{2}x^4}{2x} = 0, = x → 0 + lim ∫ 0 x x 2 cos t 2 d t − x = x → 0 + lim 2 x cos x 2 − 1 = x → 0 + lim 2 x − 2 1 x 4 = 0 , f − ′ ( 0 ) = lim x → 0 − f ( x ) − f ( 0 ) x − 0 = lim x → 0 − 2 x 2 ( 1 − cos x ) − 1 x f'_-(0) = \lim_{x \to 0^-} \frac{f(x) - f(0)}{x - 0} = \lim_{x \to 0^-} \frac{\frac{2}{x^2}(1 - \cos x) - 1}{x} f − ′ ( 0 ) = x → 0 − lim x − 0 f ( x ) − f ( 0 ) = x → 0 − lim x x 2 2 ( 1 − cos x ) − 1 = lim x → 0 − 2 ( 1 − cos x ) − x 2 x 3 = lim x → 0 − 2 sin x − 2 x 3 x 2 = lim x → 0 − 2 ( cos x − 1 ) 6 x = 0. = \lim_{x \to 0^-} \frac{2(1 - \cos x) - x^2}{x^3} = \lim_{x \to 0^-} \frac{2 \sin x - 2x}{3x^2} = \lim_{x \to 0^-} \frac{2(\cos x - 1)}{6x} = 0. = x → 0 − lim x 3 2 ( 1 − cos x ) − x 2 = x → 0 − lim 3 x 2 2 sin x − 2 x = x → 0 − lim 6 x 2 ( cos x − 1 ) = 0. 即
f + ′ ( 0 ) = f − ′ ( 0 ) = 0 f'_+(0) = f'_-(0) = 0 f + ′ ( 0 ) = f − ′ ( 0 ) = 0
,故
f ( x ) f(x) f ( x )
在
x = 0 x = 0 x = 0
处可导,且
f ′ ( 0 ) = 0 f'(0) = 0 f ′ ( 0 ) = 0
。
12 已知连续函数
f ( x ) f(x) f ( x )
满足条件
f ( x ) = ∫ 0 3 x f ( t 3 ) d t + e 2 x f(x) = \int_0^{3x} f\left(\frac{t}{3} \right) \dt + \e^{2x} f ( x ) = ∫ 0 3 x f ( 3 t ) d t + e 2 x
,求
f ( x ) f(x) f ( x )
.
【答案】 f ( x ) = 3 e 3 x − 2 e 2 x f(x) = 3e^{3x} - 2e^{2x} f ( x ) = 3 e 3 x − 2 e 2 x
【解析】 在变上限定积分令
s = t 3 s = \frac{t}{3} s = 3 t
,得到
f ( x ) = 3 ∫ 0 x f ( s ) d s + e 2 x . f(x) = 3 \int_{0}^{x} f(s) ds + e^{2x}. f ( x ) = 3 ∫ 0 x f ( s ) d s + e 2 x . 在上式中令
x = 0 x = 0 x = 0
得
f ( 0 ) = 1 f(0) = 1 f ( 0 ) = 1
,将上述两端对
x x x
求导数得
f ′ ( x ) = 3 f ( x ) + 2 e 2 x . f'(x) = 3f(x) + 2e^{2x}. f ′ ( x ) = 3 f ( x ) + 2 e 2 x . 这是一阶线性微分方程的特解问题。用
e − 3 x e^{-3x} e − 3 x
同乘方程两端,得
( f ( x ) e − 3 x ) ′ = 2 e − x . (f(x)e^{-3x})' = 2e^{-x}. ( f ( x ) e − 3 x ) ′ = 2 e − x . 积分即得
f ( x ) = C e 3 x − 2 e 2 x . f(x) = Ce^{3x} - 2e^{2x}. f ( x ) = C e 3 x − 2 e 2 x . 由
f ( 0 ) = 1 f(0) = 1 f ( 0 ) = 1
可确定常数
C = 3 C = 3 C = 3
,于是所求的函数是
f ( x ) = 3 e 3 x − 2 e 2 x . f(x) = 3e^{3x} - 2e^{2x}. f ( x ) = 3 e 3 x − 2 e 2 x . 13 将函数
y = ln ( 1 − x − 2 x 2 ) y = \ln(1 - x - 2x^2) y = ln ( 1 − x − 2 x 2 )
展成
x x x
的幂级数,并指出其收敛区间.
【答案】
y = ∑ n = 1 ∞ ( − 1 ) n − 1 − 2 n n x n , x ∈ [ − 1 2 , 1 2 ) y = \sum_{n=1}^{\infty} \frac{(-1)^{n-1} - 2^n}{n} x^n, \quad x \in \left[ -\frac{1}{2}, \frac{1}{2} \right) y = n = 1 ∑ ∞ n ( − 1 ) n − 1 − 2 n x n , x ∈ [ − 2 1 , 2 1 ) 【解析】 首先,将函数
y = ln ( 1 − x − 2 x 2 ) y = \ln(1 - x - 2x^2) y = ln ( 1 − x − 2 x 2 )
分解为
y = ln ( 1 − 2 x ) + ln ( 1 + x ) y = \ln(1 - 2x) + \ln(1 + x) y = ln ( 1 − 2 x ) + ln ( 1 + x )
,因为
1 − x − 2 x 2 = ( 1 − 2 x ) ( 1 + x ) 1 - x - 2x^2 = (1 - 2x)(1 + x) 1 − x − 2 x 2 = ( 1 − 2 x ) ( 1 + x )
。 然后,利用已知的对数级数展开:
ln ( 1 − 2 x ) = − ∑ n = 1 ∞ ( 2 x ) n n = − ∑ n = 1 ∞ 2 n x n n , ∣ 2 x ∣ < 1 ∣ x ∣ < 1 2 \ln(1 - 2x) = -\sum_{n=1}^{\infty} \frac{(2x)^n}{n} = -\sum_{n=1}^{\infty} \frac{2^n x^n}{n}, \quad |2x| < 1 \ |x| < \frac{1}{2} ln ( 1 − 2 x ) = − n = 1 ∑ ∞ n ( 2 x ) n = − n = 1 ∑ ∞ n 2 n x n , ∣2 x ∣ < 1 ∣ x ∣ < 2 1
ln ( 1 + x ) = ∑ n = 1 ∞ ( − 1 ) n − 1 x n n , ∣ x ∣ < 1 \ln(1 + x) = \sum_{n=1}^{\infty} (-1)^{n-1} \frac{x^n}{n}, \quad |x| < 1 ln ( 1 + x ) = n = 1 ∑ ∞ ( − 1 ) n − 1 n x n , ∣ x ∣ < 1 将两式相加,得到:
y = ∑ n = 1 ∞ ( − 2 n n + ( − 1 ) n − 1 1 n ) x n = ∑ n = 1 ∞ ( − 1 ) n − 1 − 2 n n x n y = \sum_{n=1}^{\infty} \left( -\frac{2^n}{n} + (-1)^{n-1} \frac{1}{n} \right) x^n = \sum_{n=1}^{\infty} \frac{(-1)^{n-1} - 2^n}{n} x^n y = n = 1 ∑ ∞ ( − n 2 n + ( − 1 ) n − 1 n 1 ) x n = n = 1 ∑ ∞ n ( − 1 ) n − 1 − 2 n x n 收敛区间由两个级数的收敛域决定。函数定义域为
1 − x − 2 x 2 > 0 1 - x - 2x^2 > 0 1 − x − 2 x 2 > 0
,即
− 1 < x < 1 2 -1 < x < \frac{1}{2} − 1 < x < 2 1
。级数的收敛半径通过系数极限求得:
lim n → ∞ ∣ a n + 1 a n ∣ = lim n → ∞ ∣ ( − 1 ) n − 2 n + 1 n + 1 ( − 1 ) n − 1 − 2 n n ∣ ≈ lim n → ∞ 2 n + 1 / n 2 n / n = 2 \lim_{n \to \infty} \left| \frac{a_{n+1}}{a_n} \right| = \lim_{n \to \infty} \left| \frac{\frac{(-1)^n - 2^{n+1}}{n+1}}{\frac{(-1)^{n-1} - 2^n}{n}} \right| \approx \lim_{n \to \infty} \frac{2^{n+1}/n}{2^n/n} = 2 n → ∞ lim a n a n + 1 = n → ∞ lim n ( − 1 ) n − 1 − 2 n n + 1 ( − 1 ) n − 2 n + 1 ≈ n → ∞ lim 2 n / n 2 n + 1 / n = 2 收敛半径为
R = 1 2 R = \frac{1}{2} R = 2 1
。在
x = 1 2 x = \frac{1}{2} x = 2 1
处,级数为
∑ ( ( − 1 ) n − 1 n 2 n − 1 n ) \sum \left( \frac{(-1)^{n-1}}{n 2^n} - \frac{1}{n} \right) ∑ ( n 2 n ( − 1 ) n − 1 − n 1 )
,其中
∑ 1 n \sum \frac{1}{n} ∑ n 1
发散,故发散。在
x = − 1 2 x = -\frac{1}{2} x = − 2 1
处,级数为
∑ ( − 1 n 2 n − ( − 1 ) n n ) \sum \left( -\frac{1}{n 2^n} - \frac{(-1)^n}{n} \right) ∑ ( − n 2 n 1 − n ( − 1 ) n )
,两者均收敛,故收敛。因此,收敛区间为
[ − 1 2 , 1 2 ) \left[ -\frac{1}{2}, \frac{1}{2} \right) [ − 2 1 , 2 1 )
。
14 计算
∫ − ∞ + ∞ ∫ − ∞ + ∞ min { x , y } e − ( x 2 + y 2 ) d x d y \int_{-\infty}^{+\infty} \int_{-\infty}^{+\infty} \min \{x,y\} \e^{- (x^2 + y^2)} \dx\dy ∫ − ∞ + ∞ ∫ − ∞ + ∞ min { x , y } e − ( x 2 + y 2 ) d x d y
.
【答案】
− π 2 -\sqrt{\frac{\pi}{2}} − 2 π 【解析】 方法一 :将积分区域
D D D
分为两部分:
D 1 = { ( x , y ) ∣ − ∞ ≤ x ≤ + ∞ , x ≤ y < + ∞ } ,
D_1 = \{(x, y)| -\infty \leq x \leq +\infty, x \leq y < +\infty\},
D 1 = {( x , y ) ∣ − ∞ ≤ x ≤ + ∞ , x ≤ y < + ∞ } ,
D 2 = { ( x , y ) ∣ − ∞ ≤ x ≤ + ∞ , − ∞ < y ≤ x } .
D_2 = \{(x, y)| -\infty \leq x \leq +\infty, -\infty < y \leq x\}.
D 2 = {( x , y ) ∣ − ∞ ≤ x ≤ + ∞ , − ∞ < y ≤ x } . 从而有
I = ∬ D 1 + D 2 min { x , y } e − ( x 2 + y 2 ) d x d y = ∬ D 1 x e − ( x 2 + y 2 ) d x d y + ∬ D 2 y e − ( x 2 + y 2 ) d x d y = ∫ − ∞ + ∞ e − y 2 d y ∫ − ∞ y x e − x 2 d x + ∫ − ∞ + ∞ e − x 2 d x ∫ − ∞ x y e − y 2 d y = − 1 2 ∫ − ∞ + ∞ e − 2 y 2 d y − 1 2 ∫ − ∞ + ∞ e − 2 x 2 d x = − ∫ − ∞ + ∞ e − 2 x 2 d x .
\begin{align*}
I &= \iint_{D_1 + D_2} \min\{x, y\} e^{-(x^2 + y^2)} \, dx \, dy \\
&= \iint_{D_1} x e^{-(x^2 + y^2)} \, dx \, dy + \iint_{D_2} y e^{-(x^2 + y^2)} \, dx \, dy \\
&= \int_{-\infty}^{+\infty} e^{-y^2} \, dy \int_{-\infty}^y x e^{-x^2} \, dx + \int_{-\infty}^{+\infty} e^{-x^2} \, dx \int_{-\infty}^x y e^{-y^2} \, dy \\
&= -\frac{1}{2} \int_{-\infty}^{+\infty} e^{-2y^2} \, dy - \frac{1}{2} \int_{-\infty}^{+\infty} e^{-2x^2} \, dx \\
&= -\int_{-\infty}^{+\infty} e^{-2x^2} \, dx.
\end{align*}
I = ∬ D 1 + D 2 min { x , y } e − ( x 2 + y 2 ) d x d y = ∬ D 1 x e − ( x 2 + y 2 ) d x d y + ∬ D 2 y e − ( x 2 + y 2 ) d x d y = ∫ − ∞ + ∞ e − y 2 d y ∫ − ∞ y x e − x 2 d x + ∫ − ∞ + ∞ e − x 2 d x ∫ − ∞ x y e − y 2 d y = − 2 1 ∫ − ∞ + ∞ e − 2 y 2 d y − 2 1 ∫ − ∞ + ∞ e − 2 x 2 d x = − ∫ − ∞ + ∞ e − 2 x 2 d x . 令
t = 2 x t = \sqrt{2}x t = 2 x
,利用泊松积分
∫ − ∞ + ∞ e − x 2 d x = π \int_{-\infty}^{+\infty} e^{-x^2} dx = \sqrt{\pi} ∫ − ∞ + ∞ e − x 2 d x = π
,则有
I = − 1 2 ∫ − ∞ + ∞ e − t 2 d t = − π 2 .
I = -\frac{1}{\sqrt{2}} \int_{-\infty}^{+\infty} e^{-t^2} dt = -\sqrt{\frac{\pi}{2}}.
I = − 2 1 ∫ − ∞ + ∞ e − t 2 d t = − 2 π . 方法二 :引入极坐标系
x = r cos θ , y = r sin θ x = r \cos \theta, y = r \sin \theta x = r cos θ , y = r sin θ
,则
3 π 4 ≤ θ ≤ π 4 ⇒ min { x , y } = y = r sin θ ,
\frac{3\pi}{4} \leq \theta \leq \frac{\pi}{4} \Rightarrow \min\{x, y\} = y = r \sin \theta,
4 3 π ≤ θ ≤ 4 π ⇒ min { x , y } = y = r sin θ ,
π 4 ≤ θ ≤ 5 π 4 ⇒ min { x , y } = x = r cos θ .
\frac{\pi}{4} \leq \theta \leq \frac{5\pi}{4} \Rightarrow \min\{x, y\} = x = r \cos \theta.
4 π ≤ θ ≤ 4 5 π ⇒ min { x , y } = x = r cos θ . 于是
I = ∫ − ∞ + ∞ ∫ − ∞ + ∞ min { x , y } e − ( x 2 + y 2 ) d x d y = ∫ − 3 π 4 π 4 sin θ d θ ∫ 0 + ∞ r 2 e − r 2 d r + ∫ π 4 5 π 4 cos θ d θ ∫ 0 + ∞ r 2 e − r 2 d r = ∫ 0 + ∞ r 2 e − r 2 d r [ ∫ − 3 π 4 π 4 sin θ d θ + ∫ π 4 5 π 4 cos θ d θ ] = − 2 2 ∫ 0 + ∞ r 2 e − r 2 d r = 2 [ r e − r 2 ∣ 0 + ∞ − ∫ 0 + ∞ e − r 2 d r ] = − 2 ∫ 0 + ∞ e − r 2 d r = − 2 ⋅ π 2 = − π 2 .
\begin{align*}
I &= \int_{-\infty}^{+\infty} \int_{-\infty}^{+\infty} \min\{x, y\} e^{-(x^2 + y^2)} \, dx \, dy \\
&= \int_{-\frac{3\pi}{4}}^{\frac{\pi}{4}} \sin\theta \, d\theta \int_{0}^{+\infty} r^2 e^{-r^2} \, dr + \int_{\frac{\pi}{4}}^{\frac{5\pi}{4}} \cos\theta \, d\theta \int_{0}^{+\infty} r^2 e^{-r^2} \, dr \\
&= \int_{0}^{+\infty} r^2 e^{-r^2} \, dr \left[ \int_{-\frac{3\pi}{4}}^{\frac{\pi}{4}} \sin\theta \, d\theta + \int_{\frac{\pi}{4}}^{\frac{5\pi}{4}} \cos\theta \, d\theta \right] \\
&= -2\sqrt{2} \int_{0}^{+\infty} r^2 e^{-r^2} \, dr \\
&= \sqrt{2} \left[ r e^{-r^2} \bigg|_{0}^{+\infty} - \int_{0}^{+\infty} e^{-r^2} \, dr \right] \\
&= -\sqrt{2} \int_{0}^{+\infty} e^{-r^2} \, dr \\
&= -\sqrt{2} \cdot \frac{\sqrt{\pi}}{2} \\
&= -\sqrt{\frac{\pi}{2}}.
\end{align*}
I = ∫ − ∞ + ∞ ∫ − ∞ + ∞ min { x , y } e − ( x 2 + y 2 ) d x d y = ∫ − 4 3 π 4 π sin θ d θ ∫ 0 + ∞ r 2 e − r 2 d r + ∫ 4 π 4 5 π cos θ d θ ∫ 0 + ∞ r 2 e − r 2 d r = ∫ 0 + ∞ r 2 e − r 2 d r [ ∫ − 4 3 π 4 π sin θ d θ + ∫ 4 π 4 5 π cos θ d θ ] = − 2 2 ∫ 0 + ∞ r 2 e − r 2 d r = 2 [ r e − r 2 0 + ∞ − ∫ 0 + ∞ e − r 2 d r ] = − 2 ∫ 0 + ∞ e − r 2 d r = − 2 ⋅ 2 π = − 2 π . 15 设某产品的需求函数为
Q = Q ( P ) Q = Q(P) Q = Q ( P )
,收益函数为
R = P Q R = PQ R = PQ
,其中
P P P
为产品价格,
Q Q Q
为需求量(产品的产量),
Q ( P ) Q(P) Q ( P )
为单调减函数.如果当价格为
P 0 P_0 P 0
,对应产量为
Q 0 Q_0 Q 0
时,边际收益
d R d Q ∣ Q = Q 0 = a > 0 \left. \frac{\d R}{\d Q} \right|_{Q = Q_0} = a > 0 d Q d R Q = Q 0 = a > 0
,
收益对价格的边际效应
d R d P ∣ P = P 0 = c < 0 \left. \frac{\d R}{\d P} \right|_{P = P_0} = c < 0 d P d R P = P 0 = c < 0
,
需求对价格的弹性
E P = b > 1 E_P = b > 1 E P = b > 1
.求
P 0 P_0 P 0
和
Q 0 Q_0 Q 0
.
【答案】
P 0 = a b b − 1 P_0 = \dfrac{a b}{b-1} P 0 = b − 1 ab
,
Q 0 = − c b − 1 Q_0 = -\dfrac{c}{b-1} Q 0 = − b − 1 c
【解析】
已知收益函数
R = P Q ( P ) R = P Q(P) R = PQ ( P )
,其中
Q ( P ) Q(P) Q ( P )
是单调减函数。在点
( P 0 , Q 0 ) (P_0, Q_0) ( P 0 , Q 0 )
处,给定边际收益
d R d Q ∣ Q = Q 0 = a > 0 \left. \frac{\d R}{\d Q} \right|_{Q=Q_0} = a > 0 d Q d R Q = Q 0 = a > 0
,收益对价格的边际效应
d R d P ∣ P = P 0 = c < 0 \left. \frac{\d R}{\d P} \right|_{P=P_0} = c < 0 d P d R P = P 0 = c < 0
,需求价格弹性
E P = b > 1 E_P = b > 1 E P = b > 1
。需求价格弹性定义为
E P = − d Q d P ⋅ P Q E_P = - \frac{\d Q}{\d P} \cdot \frac{P}{Q} E P = − d P d Q ⋅ Q P
,故在
P = P 0 P = P_0 P = P 0
时,有:
− d Q d P ∣ P = P 0 ⋅ P 0 Q 0 = b - \left. \frac{\d Q}{\d P} \right|_{P=P_0} \cdot \frac{P_0}{Q_0} = b − d P d Q P = P 0 ⋅ Q 0 P 0 = b 即:
d Q d P ∣ P = P 0 = − b Q 0 P 0 \left. \frac{\d Q}{\d P} \right|_{P=P_0} = -b \frac{Q_0}{P_0} d P d Q P = P 0 = − b P 0 Q 0 收益对价格的边际效应为:
d R d P ∣ P = P 0 = Q 0 + P 0 d Q d P ∣ P = P 0 = c \left. \frac{\d R}{\d P} \right|_{P=P_0} = Q_0 + P_0 \left. \frac{\d Q}{\d P} \right|_{P=P_0} = c d P d R P = P 0 = Q 0 + P 0 d P d Q P = P 0 = c 代入上式:
Q 0 + P 0 ( − b Q 0 P 0 ) = Q 0 ( 1 − b ) = c Q_0 + P_0 \left( -b \frac{Q_0}{P_0} \right) = Q_0 (1 - b) = c Q 0 + P 0 ( − b P 0 Q 0 ) = Q 0 ( 1 − b ) = c 解得:
Q 0 = c 1 − b = − c b − 1 Q_0 = \frac{c}{1 - b} = -\frac{c}{b - 1} Q 0 = 1 − b c = − b − 1 c 边际收益为:
d R d Q ∣ Q = Q 0 = P 0 + Q 0 d P d Q ∣ Q = Q 0 = a \left. \frac{\d R}{\d Q} \right|_{Q=Q_0} = P_0 + Q_0 \left. \frac{\d P}{\d Q} \right|_{Q=Q_0} = a d Q d R Q = Q 0 = P 0 + Q 0 d Q d P Q = Q 0 = a 由于
d P d Q ∣ Q = Q 0 = 1 d Q d P ∣ P = P 0 = − P 0 b Q 0 \left. \frac{\d P}{\d Q} \right|_{Q=Q_0} = \frac{1}{\left. \frac{\d Q}{\d P} \right|_{P=P_0}} = -\frac{P_0}{b Q_0} d Q d P Q = Q 0 = d P d Q ∣ P = P 0 1 = − b Q 0 P 0
,代入得:
P 0 + Q 0 ( − P 0 b Q 0 ) = P 0 ( 1 − 1 b ) = a P_0 + Q_0 \left( -\frac{P_0}{b Q_0} \right) = P_0 \left( 1 - \frac{1}{b} \right) = a P 0 + Q 0 ( − b Q 0 P 0 ) = P 0 ( 1 − b 1 ) = a 解得:
P 0 = a ⋅ b b − 1 = a b b − 1 P_0 = a \cdot \frac{b}{b - 1} = \frac{a b}{b - 1} P 0 = a ⋅ b − 1 b = b − 1 ab 因此,
P 0 = a b b − 1 P_0 = \dfrac{a b}{b-1} P 0 = b − 1 ab
,
Q 0 = − c b − 1 Q_0 = -\dfrac{c}{b-1} Q 0 = − b − 1 c
。
16 设
f ( x ) f(x) f ( x )
,
g ( x ) g(x) g ( x )
在区间
[ − a , a ] [- a,a] [ − a , a ]
(
a > 0 a > 0 a > 0
)上连续,
g ( x ) g(x) g ( x )
为偶函数,
且
f ( x ) f(x) f ( x )
满足条件
f ( x ) + f ( − x ) = A f(x) + f(- x) = A f ( x ) + f ( − x ) = A
(
A A A
为常数).
(1) 证明
∫ − a a f ( x ) g ( x ) d x = A ∫ 0 a g ( x ) d x \int_{- a}^a f(x)g(x)\dx = A\int_0^a g(x)\dx ∫ − a a f ( x ) g ( x ) d x = A ∫ 0 a g ( x ) d x
;
(2) 利用(I)的结论计算定积分
∫ − π 2 π 2 ∣ sin x ∣ arctan e x d x \int_{-\frac{\pi}{2}}^{\frac{\pi}{2}}|\sin x|\arctan\e^x\dx ∫ − 2 π 2 π ∣ sin x ∣ arctan e x d x
.
【答案】 π 2 \frac{\pi}{2} 2 π
【解析】
(1) 证明:考虑积分
∫ − a a f ( x ) g ( x ) d x \int_{-a}^{a} f(x)g(x) \, dx ∫ − a a f ( x ) g ( x ) d x
。将其拆分为两部分:
∫ − a a f ( x ) g ( x ) d x = ∫ − a 0 f ( x ) g ( x ) d x + ∫ 0 a f ( x ) g ( x ) d x . \int_{-a}^{a} f(x)g(x) \, dx = \int_{-a}^{0} f(x)g(x) \, dx + \int_{0}^{a} f(x)g(x) \, dx. ∫ − a a f ( x ) g ( x ) d x = ∫ − a 0 f ( x ) g ( x ) d x + ∫ 0 a f ( x ) g ( x ) d x . 在第一个积分中,令
u = − x u = -x u = − x
,则当
x = − a x = -a x = − a
时
u = a u = a u = a
,当
x = 0 x = 0 x = 0
时
u = 0 u = 0 u = 0
,且
d x = − d u dx = -du d x = − d u
。因此:
∫ − a 0 f ( x ) g ( x ) d x = ∫ a 0 f ( − u ) g ( − u ) ( − d u ) = ∫ 0 a f ( − u ) g ( u ) d u , \int_{-a}^{0} f(x)g(x) \, dx = \int_{a}^{0} f(-u)g(-u) (-du) = \int_{0}^{a} f(-u)g(u) \, du, ∫ − a 0 f ( x ) g ( x ) d x = ∫ a 0 f ( − u ) g ( − u ) ( − d u ) = ∫ 0 a f ( − u ) g ( u ) d u , 其中
g ( − u ) = g ( u ) g(-u) = g(u) g ( − u ) = g ( u )
因为
g ( x ) g(x) g ( x )
是偶函数。将变量
u u u
换回
x x x
,得:
∫ − a 0 f ( x ) g ( x ) d x = ∫ 0 a f ( − x ) g ( x ) d x . \int_{-a}^{0} f(x)g(x) \, dx = \int_{0}^{a} f(-x)g(x) \, dx. ∫ − a 0 f ( x ) g ( x ) d x = ∫ 0 a f ( − x ) g ( x ) d x . 于是原积分变为:
∫ − a a f ( x ) g ( x ) d x = ∫ 0 a f ( − x ) g ( x ) d x + ∫ 0 a f ( x ) g ( x ) d x = ∫ 0 a [ f ( − x ) + f ( x ) ] g ( x ) d x . \int_{-a}^{a} f(x)g(x) \, dx = \int_{0}^{a} f(-x)g(x) \, dx + \int_{0}^{a} f(x)g(x) \, dx = \int_{0}^{a} [f(-x) + f(x)] g(x) \, dx. ∫ − a a f ( x ) g ( x ) d x = ∫ 0 a f ( − x ) g ( x ) d x + ∫ 0 a f ( x ) g ( x ) d x = ∫ 0 a [ f ( − x ) + f ( x )] g ( x ) d x . 由条件
f ( x ) + f ( − x ) = A f(x) + f(-x) = A f ( x ) + f ( − x ) = A
,代入得:
∫ − a a f ( x ) g ( x ) d x = A ∫ 0 a g ( x ) d x . \int_{-a}^{a} f(x)g(x) \, dx = A \int_{0}^{a} g(x) \, dx. ∫ − a a f ( x ) g ( x ) d x = A ∫ 0 a g ( x ) d x . 故结论成立。
(2) 计算积分
∫ − π 2 π 2 ∣ sin x ∣ arctan e x d x \int_{-\frac{\pi}{2}}^{\frac{\pi}{2}} |\sin x| \arctan e^x \, dx ∫ − 2 π 2 π ∣ sin x ∣ arctan e x d x
。令
f ( x ) = arctan e x f(x) = \arctan e^x f ( x ) = arctan e x
,
g ( x ) = ∣ sin x ∣ g(x) = |\sin x| g ( x ) = ∣ sin x ∣
,区间
[ − a , a ] [-a, a] [ − a , a ]
中
a = π 2 a = \frac{\pi}{2} a = 2 π
。首先,
g ( x ) = ∣ sin x ∣ g(x) = |\sin x| g ( x ) = ∣ sin x ∣
是偶函数,因为
∣ sin ( − x ) ∣ = ∣ − sin x ∣ = ∣ sin x ∣ |\sin(-x)| = |-\sin x| = |\sin x| ∣ sin ( − x ) ∣ = ∣ − sin x ∣ = ∣ sin x ∣
。其次,验证
f ( x ) + f ( − x ) = A f(x) + f(-x) = A f ( x ) + f ( − x ) = A
:
f ( x ) + f ( − x ) = arctan e x + arctan e − x . f(x) + f(-x) = \arctan e^x + \arctan e^{-x}. f ( x ) + f ( − x ) = arctan e x + arctan e − x . 由于
e x > 0 e^x > 0 e x > 0
,有恒等式
arctan u + arctan 1 u = π 2 \arctan u + \arctan \frac{1}{u} = \frac{\pi}{2} arctan u + arctan u 1 = 2 π
(当
u > 0 u > 0 u > 0
),故:
arctan e x + arctan e − x = π 2 , \arctan e^x + \arctan e^{-x} = \frac{\pi}{2}, arctan e x + arctan e − x = 2 π , 即
A = π 2 A = \frac{\pi}{2} A = 2 π
。根据 (1) 的结论:
∫ − π 2 π 2 ∣ sin x ∣ arctan e x d x = A ∫ 0 π 2 ∣ sin x ∣ d x = π 2 ∫ 0 π 2 sin x d x , \int_{-\frac{\pi}{2}}^{\frac{\pi}{2}} |\sin x| \arctan e^x \, dx = A \int_{0}^{\frac{\pi}{2}} |\sin x| \, dx = \frac{\pi}{2} \int_{0}^{\frac{\pi}{2}} \sin x \, dx, ∫ − 2 π 2 π ∣ sin x ∣ arctan e x d x = A ∫ 0 2 π ∣ sin x ∣ d x = 2 π ∫ 0 2 π sin x d x , 因为在
[ 0 , π 2 ] [0, \frac{\pi}{2}] [ 0 , 2 π ]
上
sin x ≥ 0 \sin x \geq 0 sin x ≥ 0
,所以
∣ sin x ∣ = sin x |\sin x| = \sin x ∣ sin x ∣ = sin x
。计算:
∫ 0 π 2 sin x d x = [ − cos x ] 0 π 2 = − cos π 2 + cos 0 = 0 + 1 = 1. \int_{0}^{\frac{\pi}{2}} \sin x \, dx = [-\cos x]_{0}^{\frac{\pi}{2}} = -\cos \frac{\pi}{2} + \cos 0 = 0 + 1 = 1. ∫ 0 2 π sin x d x = [ − cos x ] 0 2 π = − cos 2 π + cos 0 = 0 + 1 = 1. 因此,积分值为:
π 2 × 1 = π 2 . \frac{\pi}{2} \times 1 = \frac{\pi}{2}. 2 π × 1 = 2 π . 17 已知向量组(I)
α 1 , α 2 , α 3 \alpha_1,\alpha_2,\alpha_3 α 1 , α 2 , α 3
;(II)
α 1 , α 2 , α 3 , α 4 \alpha_1,\alpha_2,\alpha_3,\alpha_4 α 1 , α 2 , α 3 , α 4
;
(III)
α 1 , α 2 , α 3 , α 5 \alpha_1,\alpha_2,\alpha_3,\alpha_5 α 1 , α 2 , α 3 , α 5
.
如果各向量组的秩分别为
r ( I ) = r ( II ) = 3 r(\textrm{I}) = r(\textrm{II}) = 3 r ( I ) = r ( II ) = 3
,
r ( III ) = 4 r(\textrm{III}) = 4 r ( III ) = 4
,
证明:向量组
α 1 , α 2 , α 3 , α 5 − α 4 \alpha_1,\alpha_2,\alpha_3,\alpha_5 - \alpha_4 α 1 , α 2 , α 3 , α 5 − α 4
的秩为4.
【答案】 向量组
α 1 , α 2 , α 3 , α 5 − α 4 \alpha_1, \alpha_2, \alpha_3, \alpha_5 - \alpha_4 α 1 , α 2 , α 3 , α 5 − α 4
的秩为 4。
【解析】 已知
r ( I ) = 3 r(\mathrm{I}) = 3 r ( I ) = 3
,即
α 1 , α 2 , α 3 \alpha_1, \alpha_2, \alpha_3 α 1 , α 2 , α 3
线性无关。 已知
r ( I I ) = 3 r(\mathrm{II}) = 3 r ( II ) = 3
,即
α 4 \alpha_4 α 4
可由
α 1 , α 2 , α 3 \alpha_1, \alpha_2, \alpha_3 α 1 , α 2 , α 3
线性表示,设
α 4 = c 1 α 1 + c 2 α 2 + c 3 α 3 \alpha_4 = c_1 \alpha_1 + c_2 \alpha_2 + c_3 \alpha_3 α 4 = c 1 α 1 + c 2 α 2 + c 3 α 3
,其中
c 1 , c 2 , c 3 c_1, c_2, c_3 c 1 , c 2 , c 3
为标量。 已知
r ( I I I ) = 4 r(\mathrm{III}) = 4 r ( III ) = 4
,即
α 1 , α 2 , α 3 , α 5 \alpha_1, \alpha_2, \alpha_3, \alpha_5 α 1 , α 2 , α 3 , α 5
线性无关。
考虑向量组
α 1 , α 2 , α 3 , α 5 − α 4 \alpha_1, \alpha_2, \alpha_3, \alpha_5 - \alpha_4 α 1 , α 2 , α 3 , α 5 − α 4
。要证明其秩为 4,只需证明该向量组线性无关。 设存在标量
k 1 , k 2 , k 3 , k 4 k_1, k_2, k_3, k_4 k 1 , k 2 , k 3 , k 4
,使得
k 1 α 1 + k 2 α 2 + k 3 α 3 + k 4 ( α 5 − α 4 ) = 0. k_1 \alpha_1 + k_2 \alpha_2 + k_3 \alpha_3 + k_4 (\alpha_5 - \alpha_4) = 0. k 1 α 1 + k 2 α 2 + k 3 α 3 + k 4 ( α 5 − α 4 ) = 0. 展开得
k 1 α 1 + k 2 α 2 + k 3 α 3 + k 4 α 5 − k 4 α 4 = 0. k_1 \alpha_1 + k_2 \alpha_2 + k_3 \alpha_3 + k_4 \alpha_5 - k_4 \alpha_4 = 0. k 1 α 1 + k 2 α 2 + k 3 α 3 + k 4 α 5 − k 4 α 4 = 0. 将
α 4 = c 1 α 1 + c 2 α 2 + c 3 α 3 \alpha_4 = c_1 \alpha_1 + c_2 \alpha_2 + c_3 \alpha_3 α 4 = c 1 α 1 + c 2 α 2 + c 3 α 3
代入,得
k 1 α 1 + k 2 α 2 + k 3 α 3 + k 4 α 5 − k 4 ( c 1 α 1 + c 2 α 2 + c 3 α 3 ) = 0. k_1 \alpha_1 + k_2 \alpha_2 + k_3 \alpha_3 + k_4 \alpha_5 - k_4 (c_1 \alpha_1 + c_2 \alpha_2 + c_3 \alpha_3) = 0. k 1 α 1 + k 2 α 2 + k 3 α 3 + k 4 α 5 − k 4 ( c 1 α 1 + c 2 α 2 + c 3 α 3 ) = 0. 整理得
( k 1 − k 4 c 1 ) α 1 + ( k 2 − k 4 c 2 ) α 2 + ( k 3 − k 4 c 3 ) α 3 + k 4 α 5 = 0. (k_1 - k_4 c_1) \alpha_1 + (k_2 - k_4 c_2) \alpha_2 + (k_3 - k_4 c_3) \alpha_3 + k_4 \alpha_5 = 0. ( k 1 − k 4 c 1 ) α 1 + ( k 2 − k 4 c 2 ) α 2 + ( k 3 − k 4 c 3 ) α 3 + k 4 α 5 = 0. 由于
α 1 , α 2 , α 3 , α 5 \alpha_1, \alpha_2, \alpha_3, \alpha_5 α 1 , α 2 , α 3 , α 5
线性无关,因此系数必须为零:
{ k 1 − k 4 c 1 = 0 , k 2 − k 4 c 2 = 0 , k 3 − k 4 c 3 = 0 , k 4 = 0. \begin{cases}
k_1 - k_4 c_1 = 0, \\
k_2 - k_4 c_2 = 0, \\
k_3 - k_4 c_3 = 0, \\
k_4 = 0.
\end{cases} ⎩ ⎨ ⎧ k 1 − k 4 c 1 = 0 , k 2 − k 4 c 2 = 0 , k 3 − k 4 c 3 = 0 , k 4 = 0. 由
k 4 = 0 k_4 = 0 k 4 = 0
代入前三个方程,得
k 1 = 0 , k 2 = 0 , k 3 = 0 k_1 = 0, k_2 = 0, k_3 = 0 k 1 = 0 , k 2 = 0 , k 3 = 0
。 因此,
k 1 = k 2 = k 3 = k 4 = 0 k_1 = k_2 = k_3 = k_4 = 0 k 1 = k 2 = k 3 = k 4 = 0
,即
α 1 , α 2 , α 3 , α 5 − α 4 \alpha_1, \alpha_2, \alpha_3, \alpha_5 - \alpha_4 α 1 , α 2 , α 3 , α 5 − α 4
线性无关,故其秩为 4。
18 已知二次型
f ( x 1 , x 2 , x 3 ) = 4 x 2 2 − 3 x 3 2 + 4 x 1 x 2 − 4 x 1 x 3 + 8 x 2 x 3 f(x_1,x_2,x_3) = 4x_2^2- 3x_3^2+ 4x_1x_2 - 4x_1x_3 + 8x_2x_3 f ( x 1 , x 2 , x 3 ) = 4 x 2 2 − 3 x 3 2 + 4 x 1 x 2 − 4 x 1 x 3 + 8 x 2 x 3
.
(1) 写出二次型
f f f
的矩阵表达式;
(2) 用正交变换把二次型
f f f
化为标准形,并写出相应的正交矩阵.
【答案】 (1) 二次型
f f f
的矩阵表达式为
f ( x ) = x T A x f(\mathbf{x}) = \mathbf{x}^T A \mathbf{x} f ( x ) = x T A x
,其中
A = ( 0 2 − 2 2 4 4 − 2 4 − 3 ) A = \begin{pmatrix}
0 & 2 & -2 \\
2 & 4 & 4 \\ -2 & 4 & -3
\end{pmatrix} A = 0 2 − 2 2 4 4 − 2 4 − 3 (2) 通过正交变换,二次型
f f f
化为标准形
y 1 2 + 6 y 2 2 − 6 y 3 2 y_1^2 + 6y_2^2 - 6y_3^2 y 1 2 + 6 y 2 2 − 6 y 3 2
,相应的正交矩阵为
Q = ( − 2 5 1 30 1 6 0 5 30 − 1 6 1 5 2 30 2 6 ) Q = \begin{pmatrix} -\frac{2}{\sqrt{5}} & \frac{1}{\sqrt{30}} & \frac{1}{\sqrt{6}} \\
0 & \frac{5}{\sqrt{30}} & -\frac{1}{\sqrt{6}} \\
\frac{1}{\sqrt{5}} & \frac{2}{\sqrt{30}} & \frac{2}{\sqrt{6}}
\end{pmatrix} Q = − 5 2 0 5 1 30 1 30 5 30 2 6 1 − 6 1 6 2 【解析】 (1) 二次型
f ( x 1 , x 2 , x 3 ) = 4 x 2 2 − 3 x 3 2 + 4 x 1 x 2 − 4 x 1 x 3 + 8 x 2 x 3 f(x_1,x_2,x_3) = 4x_2^2 - 3x_3^2 + 4x_1x_2 - 4x_1x_3 + 8x_2x_3 f ( x 1 , x 2 , x 3 ) = 4 x 2 2 − 3 x 3 2 + 4 x 1 x 2 − 4 x 1 x 3 + 8 x 2 x 3
的矩阵
A A A
是对称矩阵,其中
a 11 = 0 a_{11} = 0 a 11 = 0
(无
x 1 2 x_1^2 x 1 2
项),
a 22 = 4 a_{22} = 4 a 22 = 4
,
a 33 = − 3 a_{33} = -3 a 33 = − 3
,交叉项系数对应
2 a 12 = 4 2a_{12} = 4 2 a 12 = 4
得
a 12 = 2 a_{12} = 2 a 12 = 2
,
2 a 13 = − 4 2a_{13} = -4 2 a 13 = − 4
得
a 13 = − 2 a_{13} = -2 a 13 = − 2
,
2 a 23 = 8 2a_{23} = 8 2 a 23 = 8
得
a 23 = 4 a_{23} = 4 a 23 = 4
,故
A = ( 0 2 − 2 2 4 4 − 2 4 − 3 ) A = \begin{pmatrix}
0 & 2 & -2 \\
2 & 4 & 4 \\ -2 & 4 & -3
\end{pmatrix} A = 0 2 − 2 2 4 4 − 2 4 − 3 (2) 求矩阵
A A A
的特征值和特征向量。解特征方程
det ( A − λ I ) = 0 \det(A - \lambda I) = 0 det ( A − λ I ) = 0
:
det ( − λ 2 − 2 2 4 − λ 4 − 2 4 − 3 − λ ) = − λ 3 + λ 2 + 36 λ − 36 = 0 \det \begin{pmatrix} -\lambda & 2 & -2 \\
2 & 4-\lambda & 4 \\ -2 & 4 & -3-\lambda
\end{pmatrix} = -\lambda^3 + \lambda^2 + 36\lambda - 36 = 0 det − λ 2 − 2 2 4 − λ 4 − 2 4 − 3 − λ = − λ 3 + λ 2 + 36 λ − 36 = 0 解得
λ = 1 , 6 , − 6 \lambda = 1, 6, -6 λ = 1 , 6 , − 6
。 求特征向量:
对
λ = 1 \lambda = 1 λ = 1
,解
( A − I ) v = 0 (A - I)\mathbf{v} = 0 ( A − I ) v = 0
,得
v 1 = ( − 2 , 0 , 1 ) T \mathbf{v}_1 = (-2, 0, 1)^T v 1 = ( − 2 , 0 , 1 ) T
。 对
λ = 6 \lambda = 6 λ = 6
,解
( A − 6 I ) v = 0 (A - 6I)\mathbf{v} = 0 ( A − 6 I ) v = 0
,得
v 2 = ( 1 , 5 , 2 ) T \mathbf{v}_2 = (1, 5, 2)^T v 2 = ( 1 , 5 , 2 ) T
。 对
λ = − 6 \lambda = -6 λ = − 6
,解
( A + 6 I ) v = 0 (A + 6I)\mathbf{v} = 0 ( A + 6 I ) v = 0
,得
v 3 = ( 1 , − 1 , 2 ) T \mathbf{v}_3 = (1, -1, 2)^T v 3 = ( 1 , − 1 , 2 ) T
。 特征向量相互正交。单位化: ∥ v 1 ∥ = 5 \|\mathbf{v}_1\| = \sqrt{5} ∥ v 1 ∥ = 5
,得
u 1 = 1 5 ( − 2 , 0 , 1 ) T \mathbf{u}_1 = \frac{1}{\sqrt{5}}(-2, 0, 1)^T u 1 = 5 1 ( − 2 , 0 , 1 ) T
。∥ v 2 ∥ = 30 \|\mathbf{v}_2\| = \sqrt{30} ∥ v 2 ∥ = 30
,得
u 2 = 1 30 ( 1 , 5 , 2 ) T \mathbf{u}_2 = \frac{1}{\sqrt{30}}(1, 5, 2)^T u 2 = 30 1 ( 1 , 5 , 2 ) T
。∥ v 3 ∥ = 6 \|\mathbf{v}_3\| = \sqrt{6} ∥ v 3 ∥ = 6
,得
u 3 = 1 6 ( 1 , − 1 , 2 ) T \mathbf{u}_3 = \frac{1}{\sqrt{6}}(1, -1, 2)^T u 3 = 6 1 ( 1 , − 1 , 2 ) T
。 正交矩阵
Q Q Q
以
u 1 , u 2 , u 3 \mathbf{u}_1, \mathbf{u}_2, \mathbf{u}_3 u 1 , u 2 , u 3
为列向量,标准形为
y 1 2 + 6 y 2 2 − 6 y 3 2 y_1^2 + 6y_2^2 - 6y_3^2 y 1 2 + 6 y 2 2 − 6 y 3 2
。19 假设一厂家生产的每台仪器,以概率
0.70 0.70 0.70
可以直接出厂;
以概率
0.30 0.30 0.30
需进一步调试,经调试后以概率
0.80 0.80 0.80
可以出厂;以概率
0.20 0.20 0.20
定为不合格品不能出厂.
现该厂新生产了
n n n
(
n ≥ 2 n \ge 2 n ≥ 2
)台仪器(假设各台仪器的生产过程相互独立).求:
(1) 全部能出厂的概率
α \alpha α
;
(2) 其中恰好有两台不能出厂的概率
β \beta β
;
(3) 其中至少有两台不能出厂的概率
θ \theta θ
.
【答案】 (1)
α = ( 0.94 ) n \alpha = (0.94)^n α = ( 0.94 ) n (2)
β = ( n 2 ) ( 0.06 ) 2 ( 0.94 ) n − 2 \beta = \binom{n}{2} (0.06)^2 (0.94)^{n-2} β = ( 2 n ) ( 0.06 ) 2 ( 0.94 ) n − 2 (3)
θ = 1 − ( 0.94 ) n − n ⋅ 0.06 ⋅ ( 0.94 ) n − 1 \theta = 1 - (0.94)^n - n \cdot 0.06 \cdot (0.94)^{n-1} θ = 1 − ( 0.94 ) n − n ⋅ 0.06 ⋅ ( 0.94 ) n − 1
【解析】 首先,计算每台仪器能出厂的概率:
直接出厂概率为
0.70 0.70 0.70 需调试的概率为
0.30 0.30 0.30
,调试后出厂的概率为
0.80 0.80 0.80 最终能出厂的概率为
0.70 + 0.30 × 0.80 = 0.94
0.70 + 0.30 \times 0.80 = 0.94
0.70 + 0.30 × 0.80 = 0.94
不能出厂的概率为
0.30 × 0.20 = 0.06
0.30 \times 0.20 = 0.06
0.30 × 0.20 = 0.06 设
X X X
为不能出厂的台数,则
X ∼ Binomial ( n , 0.06 ) X \sim \text{Binomial}(n, 0.06) X ∼ Binomial ( n , 0.06 )
。
(1) 全部能出厂的概率:
α = ( 0.94 ) n
\alpha = (0.94)^n
α = ( 0.94 ) n (2) 恰好两台不能出厂的概率:
β = ( n 2 ) ( 0.06 ) 2 ( 0.94 ) n − 2
\beta = \binom{n}{2} (0.06)^2 (0.94)^{n-2}
β = ( 2 n ) ( 0.06 ) 2 ( 0.94 ) n − 2 (3) 至少两台不能出厂的概率:
θ = 1 − ( 0.94 ) n − n ⋅ 0.06 ⋅ ( 0.94 ) n − 1
\theta = 1 - (0.94)^n - n \cdot 0.06 \cdot (0.94)^{n-1}
θ = 1 − ( 0.94 ) n − n ⋅ 0.06 ⋅ ( 0.94 ) n − 1 20 已知随机变量
X X X
和
Y Y Y
的联合概率密度为
f ( x , y ) = { 4 x y , 0 ≤ x ≤ 1 , 0 ≤ y ≤ 1 , 0 , 其他 , f(x,y) = \begin{cases}
4xy, & 0 \le x \le 1,0 \le y \le 1, \\
0, & \text{其他},
\end{cases} f ( x , y ) = { 4 x y , 0 , 0 ≤ x ≤ 1 , 0 ≤ y ≤ 1 , 其他 , 求
X X X
和
Y Y Y
联合分布函数
F ( x , y ) F(x,y) F ( x , y )
.
【答案】
F ( x , y ) = { 0 x < 0 y < 0 x 2 y 2 0 ≤ x ≤ 1 , 0 ≤ y ≤ 1 x 2 0 ≤ x ≤ 1 , y > 1 y 2 x > 1 , 0 ≤ y ≤ 1 1 x > 1 , y > 1 F(x,y) =
\begin{cases}
0 & \text{ } x < 0 \text{ } y < 0 \\
x^2 y^2 & \text{ } 0 \le x \le 1, 0 \le y \le 1 \\
x^2 & \text{ } 0 \le x \le 1, y > 1 \\
y^2 & \text{ } x > 1, 0 \le y \le 1 \\
1 & \text{ } x > 1, y > 1
\end{cases} F ( x , y ) = ⎩ ⎨ ⎧ 0 x 2 y 2 x 2 y 2 1 x < 0 y < 0 0 ≤ x ≤ 1 , 0 ≤ y ≤ 1 0 ≤ x ≤ 1 , y > 1 x > 1 , 0 ≤ y ≤ 1 x > 1 , y > 1 【解析】 将整个平面分为五个区域(如下图):
(Ⅰ) 当
( x , y ) ∈ D 0 (x, y) \in D_0 ( x , y ) ∈ D 0
,即
x < 0 x < 0 x < 0
或
y < 0 y < 0 y < 0
时,
F ( x , y ) = 0 F(x, y) = 0 F ( x , y ) = 0
。
(Ⅱ) 当
( x , y ) ∈ D 1 (x, y) \in D_1 ( x , y ) ∈ D 1
,即
0 ≤ x ≤ 1 0 \leq x \leq 1 0 ≤ x ≤ 1
且
0 ≤ y ≤ 1 0 \leq y \leq 1 0 ≤ y ≤ 1
时,
F ( x , y ) = ∫ 0 x ∫ 0 y 4 s t d t d s = ∫ 0 x 2 s y 2 d s = x 2 y 2 .
F(x, y) = \int_{0}^{x} \int_{0}^{y} 4st \, dt \, ds = \int_{0}^{x} 2sy^2 \, ds = x^2 y^2.
F ( x , y ) = ∫ 0 x ∫ 0 y 4 s t d t d s = ∫ 0 x 2 s y 2 d s = x 2 y 2 . (Ⅲ) 当
( x , y ) ∈ D 2 (x, y) \in D_2 ( x , y ) ∈ D 2
,即
0 ≤ x ≤ 1 0 \leq x \leq 1 0 ≤ x ≤ 1
且
y > 1 y > 1 y > 1
时,
F ( x , y ) = ∫ 0 x ∫ 0 y 4 s t d t d s = ∫ 0 x d s ∫ 0 1 4 s t d t = ∫ 0 x 2 s d s = x 2 .
F(x, y) = \int_{0}^{x} \int_{0}^{y} 4st \, dt \, ds = \int_{0}^{x} ds \int_{0}^{1} 4st \, dt = \int_{0}^{x} 2s \, ds = x^2.
F ( x , y ) = ∫ 0 x ∫ 0 y 4 s t d t d s = ∫ 0 x d s ∫ 0 1 4 s t d t = ∫ 0 x 2 s d s = x 2 . (Ⅳ) 当
( x , y ) ∈ D 3 (x, y) \in D_3 ( x , y ) ∈ D 3
,即
x > 1 x > 1 x > 1
且
0 ≤ y ≤ 1 0 \leq y \leq 1 0 ≤ y ≤ 1
时,与
D 2 D_2 D 2
类似,有
F ( x , y ) = y 2 F(x, y) = y^2 F ( x , y ) = y 2
。
(Ⅴ) 当
( x , y ) ∈ D 4 (x, y) \in D_4 ( x , y ) ∈ D 4
,即
x > 1 x > 1 x > 1
且
y > 1 y > 1 y > 1
时,
F ( x , y ) = 1 F(x, y) = 1 F ( x , y ) = 1
。