2025 National Graduate Entrance Examination Mathematics I Past Paper

Part I: Multiple Choice

Part I: Multiple Choice: Questions 1-10, 5 points each, 50 points in total. Of the four options given in each of the following questions, only one satisfies the requirement of the question.

1. Given the functions f(x)=∫0xet2sin⁡t dtf(x) = \int_0^x e^{t^2} \sin t\,dt, g(x)=∫0xet2dt⋅sin⁡2xg(x) = \int_0^x e^{t^2} dt \cdot \sin^2 x, then

A. x=0x=0 is an extremum point of f(x)f(x), and also an extremum point of g(x)g(x).

B. x=0x=0 is an extremum point of f(x)f(x), and (0,0)(0,0) is an inflection point of the curve y=g(x)y=g(x).

C. x=0x=0 is an extremum point of f(x)f(x), and (0,0)(0,0) is an inflection point of the curve y=f(x)y=f(x).

D. (0,0)(0,0) is an inflection point of the curve y=f(x)y=f(x), and (0,0)(0,0) is also an inflection point of the curve y=g(x)y=g(x).

extremum pointinflection pointderivativeintegral

Approach:

Differentiate f(x)f(x) and g(x)g(x) separately and judge whether x=0x=0 is an extremum point or an inflection point.

Steps:

  1. f′(x)=ex2sin⁡xf'(x) = e^{x^2} \sin x
  2. f′′(x)=2xex2sin⁡x+ex2cos⁡xf''(x) = 2x e^{x^2} \sin x + e^{x^2} \cos x
  3. f′(0)=0, f′′(0)=1>0f'(0) = 0,\ f''(0) = 1 > 0, so x=0x=0 is an extremum point of f(x)f(x).
  4. g(x)=∫0xet2dt⋅sin⁡2xg(x) = \int_0^x e^{t^2} dt \cdot \sin^2 x
  5. g′(x)=ex2sin⁡2x+sin⁡2x∫0xet2dtg'(x) = e^{x^2} \sin^2 x + \sin 2x \int_0^x e^{t^2} dt
  6. g′′(x)=ex2sin⁡2x+2xex2sin⁡2x+sin⁡2xex2+2cos⁡2x∫0xet2dtg''(x) = e^{x^2} \sin 2x + 2x e^{x^2} \sin^2 x + \sin 2x e^{x^2} + 2\cos 2x \int_0^x e^{t^2} dt
  7. g′(0)=0, g′′(0)=0, g′′′(0)>0g'(0) = 0,\ g''(0) = 0,\ g'''(0) > 0, so (0,0)(0,0) is an inflection point of y=g(x)y=g(x).

Answer:

B

2. Given the series: (1) ∑n=1∞sin⁡n3πn2+1\sum\limits_{n=1}^{\infty} \sin \dfrac{n^3\pi}{n^2+1}; (2) ∑n=1∞(−1)n(1n23−tan⁡1n23)\sum\limits_{n=1}^{\infty} (-1)^n \left( \dfrac{1}{\sqrt[3]{n^2}} - \tan \dfrac{1}{\sqrt[3]{n^2}} \right), then

A. Both (1) and (2) converge conditionally.

B. (1) converges conditionally and (2) converges absolutely.

C. (1) converges absolutely and (2) converges conditionally.

D. Both (1) and (2) converge absolutely.

convergence of a seriesabsolute convergenceconditional convergencealternating series

Approach:

Judge the convergence of the two series separately.

Steps:

  1. ∣sin⁡n3πn2+1∣=∣sin⁡(n3πn2+1−nπ)∣=∣sin⁡(nn2+1π)∣∼∣nn2+1π∣∼1n\left| \sin \dfrac{n^3\pi}{n^2+1} \right| = \left| \sin \left( \dfrac{n^3\pi}{n^2+1} - n\pi \right) \right| = \left| \sin \left( \dfrac{n}{n^2+1} \pi \right) \right| \sim \left| \dfrac{n}{n^2+1} \pi \right| \sim \dfrac{1}{n}.
  2. The series ∑n=1∞1n\sum\limits_{n=1}^{\infty} \dfrac{1}{n} diverges, so it is not absolutely convergent.
  3. sin⁡n3πn2+1=(−1)nsin⁡(n3πn2+1−nπ)=(−1)nsin⁡nn2+1π\sin \dfrac{n^3\pi}{n^2+1} = (-1)^n \sin \left( \dfrac{n^3\pi}{n^2+1} - n\pi \right) = (-1)^n \sin \dfrac{n}{n^2+1} \pi, which is an alternating series.
  4. The sequence sin⁡nn2+1π\sin \dfrac{n}{n^2+1} \pi is decreasing, so the series converges conditionally.
  5. ∑n=1∞(−1)n(1n23−tan⁡1n23)\sum\limits_{n=1}^{\infty} (-1)^n \left( \dfrac{1}{\sqrt[3]{n^2}} - \tan \dfrac{1}{\sqrt[3]{n^2}} \right).
  6. ∣(−1)n(1n23−tan⁡1n23)∣=∣1n23−tan⁡1n23∣=13n2+o(1n2)\left| (-1)^n \left( \dfrac{1}{\sqrt[3]{n^2}} - \tan \dfrac{1}{\sqrt[3]{n^2}} \right) \right| = \left| \dfrac{1}{\sqrt[3]{n^2}} - \tan \dfrac{1}{\sqrt[3]{n^2}} \right| = \dfrac{1}{3n^2} + o\left( \dfrac{1}{n^2} \right).
  7. The series ∑n=1∞1n2\sum\limits_{n=1}^{\infty} \dfrac{1}{n^2} converges, so ∑n=1∞(−1)n(1n23−tan⁡1n23)\sum\limits_{n=1}^{\infty} (-1)^n \left( \dfrac{1}{\sqrt[3]{n^2}} - \tan \dfrac{1}{\sqrt[3]{n^2}} \right) converges absolutely.

Answer:

B

3. Let the function f(x)f(x) be differentiable on the interval (0,+∞)(0,+\infty), then

A. When lim⁡x→+∞f(x)\lim\limits_{x\to+\infty} f(x) exists, lim⁡x→+∞f′(x)\lim\limits_{x\to+\infty} f'(x) exists.

B. When lim⁡x→+∞f′(x)\lim\limits_{x\to+\infty} f'(x) exists, lim⁡x→+∞f(x)\lim\limits_{x\to+\infty} f(x) exists.

C. When lim⁡x→+∞∫0xf(t)dtx\lim\limits_{x\to+\infty} \dfrac{\int_0^x f(t)dt}{x} exists, lim⁡x→+∞f(x)\lim\limits_{x\to+\infty} f(x) exists.

D. When lim⁡x→+∞f(x)\lim\limits_{x\to+\infty} f(x) exists, lim⁡x→+∞∫0xf(t)dtx\lim\limits_{x\to+\infty} \dfrac{\int_0^x f(t)dt}{x} exists.

limitderivativeintegralL'Hopital's rule

Approach:

This question tests the logical relations between the limit of a function, the limit of its derivative and the limit of its integral average. All four options are statements of the form “the existence of one limit implies the existence of another limit”; they can be judged one by one, and counterexamples are constructed where necessary.

Steps:

  1. For option A: take f(x)=sin⁡x2xf(x)=\dfrac{\sin x^2}{x}; then lim⁡x→+∞f(x)=0\lim\limits_{x\to+\infty}f(x)=0 exists, but f′(x)=2x2cos⁡x2−sin⁡x2x2f'(x)=\dfrac{2x^2\cos x^2-\sin x^2}{x^2} has no limit as x→+∞x\to+\infty, so A is wrong.
  2. For option B: take f(x)=xf(x)=\sqrt{x}; then f′(x)=12x→0f'(x)=\dfrac{1}{2\sqrt{x}}\to0 exists, but lim⁡x→+∞f(x)=+∞\lim\limits_{x\to+\infty}f(x)=+\infty does not exist, so B is wrong.
  3. For option C: take f(x)=cos⁡xf(x)=\cos x; then lim⁡x→+∞∫0xf(t)dtx=lim⁡x→+∞sin⁡xx=0\lim\limits_{x\to+\infty}\dfrac{\int_0^xf(t)dt}{x}=\lim\limits_{x\to+\infty}\dfrac{\sin x}{x}=0 exists, but lim⁡x→+∞f(x)\lim\limits_{x\to+\infty}f(x) does not exist, so C is wrong.
  4. For option D: if A=lim⁡x→+∞f(x)A=\lim\limits_{x\to+\infty}f(x) exists, then by L’Hopital’s rule lim⁡x→+∞∫0xf(t)dtx=lim⁡x→+∞f(x)1=A\displaystyle\lim_{x\to+\infty}\frac{\int_0^xf(t)dt}{x}=\lim_{x\to+\infty}\frac{f(x)}{1}=A exists, so D is correct, and D is the correct choice.

Answer:

D

4. Let the function f(x,y)f(x,y) be continuous. Then ∫−22dx∫4−x24f(x,y)dy=\int_{-2}^2 dx \int_{4-x^2}^4 f(x,y)dy=

A. ∫04dy∫−4−y4−yf(x,y)dx+∫−20dx∫4−x24f(x,y)dy\int_0^4 dy \int_{-\sqrt{4-y}}^{\sqrt{4-y}} f(x,y)dx + \int_{-2}^0 dx \int_{4-x^2}^4 f(x,y)dy.

B. ∫04[∫−4−y2f(x,y)dx+∫24−yf(x,y)dx]dy\int_0^4 \left[ \int_{-\sqrt{4-y}}^2 f(x,y)dx + \int_2^{\sqrt{4-y}} f(x,y)dx \right]dy.

C. ∫04[∫−4−y2f(x,y)dx+∫4−y2f(x,y)dx]dy\int_0^4 \left[ \int_{-\sqrt{4-y}}^2 f(x,y)dx + \int_{\sqrt{4-y}}^2 f(x,y)dx \right]dy.

D. 2∫04dy∫4−y2f(x,y)dx2\int_0^4 dy \int_{\sqrt{4-y}}^2 f(x,y)dx.

double integralregion of integrationinterchange of the order of integration

Approach:

This question tests the interchange of the order of integration of a double integral. First determine the region of integration, then split the region into two parts according to the sign of xx, and interchange the order of integration in one of them.

Steps:

  1. From the original expression ∫−22dx∫4−x24f(x,y)dy\displaystyle\int_{-2}^2dx\int_{4-x^2}^4f(x,y)dy we see that the region of integration is D={(x,y)∣4−x2≤y≤4, −2≤x≤2}D=\{(x,y)\mid 4-x^2\le y\le4,\ -2\le x\le2\}.
  2. Denote D1={(x,y)∣4−x2≤y≤4, −2≤x≤0}D_1=\{(x,y)\mid 4-x^2\le y\le4,\ -2\le x\le0\}, D2={(x,y)∣4−x2≤y≤4, 0≤x≤2}D_2=\{(x,y)\mid 4-x^2\le y\le4,\ 0\le x\le2\}; then I=∬D1f dσ+∬D2f dσI=\iint_{D_1}f\,d\sigma+\iint_{D_2}f\,d\sigma.
  3. Interchange the order of integration for D2D_2: with yy fixed, −x2+y−4≤0-x^2+y-4\le0 means x2≥4−yx^2\ge4-y, and combined with 0≤x≤20\le x\le2 this gives 4−y≤x≤2\sqrt{4-y}\le x\le2, and 0≤y≤40\le y\le4, so ∬D2f dσ=∫04dy∫4−y2f(x,y)dx\displaystyle\iint_{D_2}f\,d\sigma=\int_0^4dy\int_{\sqrt{4-y}}^2f(x,y)dx.
  4. Meanwhile ∬D1f dσ=∫−20dx∫4−x24f(x,y)dy\displaystyle\iint_{D_1}f\,d\sigma=\int_{-2}^0dx\int_{4-x^2}^4f(x,y)dy keeps the original order.
  5. Adding the two gives the expression of option (A), so (A) is the correct choice.

Answer:

A

5. The positive index of inertia of the quadratic form f(x1,x2,x3)=x12+2x1x2+2x1x3f(x_1,x_2,x_3)=x_1^2+2x_1x_2+2x_1x_3 is

A. 0.

B. 1.

C. 2.

D. 3.

quadratic formeigenvalueindex of inertiamatrix

Approach:

This question tests the positive index of inertia of a quadratic form. The positive index of inertia equals the number of positive eigenvalues of the matrix of the quadratic form, so it is enough to find the eigenvalues.

Steps:

  1. The matrix of the quadratic form is A=(111100100)A=\begin{pmatrix}1&1&1\\1&0&0\\1&0&0\end{pmatrix}.
  2. Compute the characteristic polynomial: ∣λE−A∣=∣λ−1−1−1−1λ0−10λ∣=λ[λ(λ−1)−1−1]=λ(λ2−λ−2)|\lambda E-A|=\begin{vmatrix}\lambda-1&-1&-1\\-1&\lambda&0\\-1&0&\lambda\end{vmatrix}=\lambda\bigl[\lambda(\lambda-1)-1-1\bigr]=\lambda(\lambda^2-\lambda-2).
  3. Factoring gives ∣λE−A∣=λ(λ−2)(λ+1)|\lambda E-A|=\lambda(\lambda-2)(\lambda+1), so the eigenvalues are λ1=0, λ2=2, λ3=−1\lambda_1=0,\ \lambda_2=2,\ \lambda_3=-1.
  4. There is only one positive eigenvalue, namely λ2=2\lambda_2=2, so the positive index of inertia is 1, and (B) is the correct choice.

Answer:

B

6. Let α1,α2,α3,α4\alpha_1,\alpha_2,\alpha_3,\alpha_4 be nn-dimensional column vectors, with α1,α2\alpha_1,\alpha_2 linearly independent, α1,α2,α3\alpha_1,\alpha_2,\alpha_3 linearly dependent, and α1+α2+α4=0\alpha_1+\alpha_2+\alpha_4=0. In the rectangular coordinate system O−xyzO-xyz in space, the geometric figure described by the system of equations in x,y,zx,y,z xα1+yα2+zα3=α4x\alpha_1+y\alpha_2+z\alpha_3=\alpha_4 is

A. A plane through the origin.

B. A straight line through the origin.

C. A plane not passing through the origin.

D. A straight line not passing through the origin.

vectorlinear dependencematrix rankgeometric figure

Approach:

This question tests the geometric meaning of the solution set of a system of linear equations and the rank of a matrix. First the ranks of the coefficient matrix and of the augmented matrix are obtained from the linear relations among the vectors, and then it is decided whether the solution set is a plane or a straight line.

Steps:

  1. Denote A=(α1,α2,α3)A=(\alpha_1,\alpha_2,\alpha_3). Since α1,α2\alpha_1,\alpha_2 are linearly independent while α1,α2,α3\alpha_1,\alpha_2,\alpha_3 are linearly dependent, r(A)=2r(A)=2.
  2. Denote A‾=(α1,α2,α3,α4)\overline A=(\alpha_1,\alpha_2,\alpha_3,\alpha_4); from α1+α2+α4=0\alpha_1+\alpha_2+\alpha_4=0 we know that α4\alpha_4 can be represented as a linear combination of α1,α2\alpha_1,\alpha_2, so r(A‾)=2r(\overline A)=2.
  3. Hence Ax=α4Ax=\alpha_4 has infinitely many solutions, and the solution set is described by xα1+yα2+zα3=α4x\alpha_1+y\alpha_2+z\alpha_3=\alpha_4, which is a plane in space.
  4. Moreover, if that plane passed through the origin, then α4=0\alpha_4=0, which contradicts the linear independence of α1,α2\alpha_1,\alpha_2, so the plane does not pass through the origin.
  5. Hence its geometric figure is a plane not passing through the origin, and (D) is the correct choice.

Answer:

D

7. Let nn be the order of the matrices A,B,CA,B,C, which satisfy r(A)+r(B)+r(C)=r(ABC)+2nr(A)+r(B)+r(C)=r(ABC)+2n. The following four conclusions are given:

(1) r(ABC)+n=r(AB)+r(C)r(ABC)+n=r(AB)+r(C);

(2) r(AB)+n=r(A)+r(B)r(AB)+n=r(A)+r(B);

(3) r(A)=r(B)=r(C)=nr(A)=r(B)=r(C)=n;

(4) r(AB)=r(BC)=nr(AB)=r(BC)=n.

The numbers of the correct conclusions are

A. (1) and (2).

B. (1) and (3).

C. (2) and (4).

D. (3) and (4).

matrix rankmatrix operationlinear algebra

Approach:

This question tests the operational rules for the rank of a matrix and the verification of the conclusions by counterexamples. As soon as one of the four conclusions fails to hold, a matrix satisfying the condition can be constructed to rule it out.

Steps:

  1. Take A=(100000000)A=\begin{pmatrix}1&0&0\\0&0&0\\0&0&0\end{pmatrix}, B=(001010100)B=\begin{pmatrix}0&0&1\\0&1&0\\1&0&0\end{pmatrix}, C=EC=E; then r(A)=1, r(B)=1, r(C)=3r(A)=1,\ r(B)=1,\ r(C)=3, and ABC=BABC=B, r(ABC)=1r(ABC)=1.
  2. Check the condition: r(A)+r(B)+r(C)=1+1+3=5r(A)+r(B)+r(C)=1+1+3=5, whereas r(ABC)+2n=1+6=7r(ABC)+2n=1+6=7.
  3. Conclusion (3) gives r(A)=r(B)=r(C)=nr(A)=r(B)=r(C)=n, that is all three equal 3, which contradicts r(A)=1, r(B)=1r(A)=1,\ r(B)=1 in the example above, so (3) does not hold.
  4. Conclusion (4) gives r(AB)=r(BC)=nr(AB)=r(BC)=n, whereas in the example above AB=0AB=0 gives r(AB)=0r(AB)=0 and BC=BBC=B gives r(BC)=1r(BC)=1, neither of which equals 3, so (4) does not hold.
  5. Hence the correct conclusions can only be (1) and (2), that is option (A) is the correct choice.

Answer:

A

8. Let the two-dimensional random variable (X,Y)(X,Y) follow the normal distribution N(0,0;1,1;ρ)N(0,0;1,1;\rho), where ρ∈(−1,1)\rho\in(-1,1). If a,ba,b are arbitrary real numbers satisfying a2+b2=1a^2+b^2=1, then the maximum of D(aX+bY)D(aX+bY) is

A. 1.

B. 2.

C. 1+∣ρ∣1+|\rho|.

D. 1+ρ21+\rho^2.

probability theorynormal distributionvarianceextremum

Approach:

This question tests the variance and the maximum of a linear combination of a two-dimensional normal distribution. Write D(aX+bY)D(aX+bY) as a function of aa, and then find its maximum under the constraint a2+b2=1a^2+b^2=1.

Steps:

  1. From D(X)=D(Y)=1D(X)=D(Y)=1 and Cov(X,Y)=ρ\mathrm{Cov}(X,Y)=\rho, we get D(aX+bY)=a2DX+b2DY+2ab Cov(X,Y)=a2+b2+2abρD(aX+bY)=a^2DX+b^2DY+2ab\,\mathrm{Cov}(X,Y)=a^2+b^2+2ab\rho.
  2. From a2+b2=1a^2+b^2=1, we get D(aX+bY)=1+2abρD(aX+bY)=1+2ab\rho.
  3. From a2+b2=1a^2+b^2=1 we know that ∣ab∣≤12|ab|\le\dfrac12, with equality when a2=b2=12a^2=b^2=\dfrac12, so the maximum of 2abρ2ab\rho is ∣ρ∣|\rho|.
  4. Hence the maximum of D(aX+bY)D(aX+bY) is 1+∣ρ∣1+|\rho|, and (C) is the correct choice.

Answer:

C

9. Let X1,X2,⋯ ,X20X_1,X_2,\cdots,X_{20} be a simple random sample from the population B(1,0.1)B(1,0.1). Put T=∑i=120XiT=\sum\limits_{i=1}^{20} X_i. Using the method of approximating a binomial distribution by a Poisson distribution, we get P{T≤1}≈P\{T\leq 1\}\approx

A. 1e2\frac{1}{e^2}.

B. 2e2\frac{2}{e^2}.

C. 3e2\frac{3}{e^2}.

D. 4e2\frac{4}{e^2}.

probability theorybinomial distributionPoisson distributionprobability calculation

Approach:

This question tests the approximation of a binomial distribution by a Poisson distribution. When nn is large and pp is small, B(n,p)B(n,p) can be approximated by a Poisson distribution with parameter npnp.

Steps:

  1. T=∑i=120Xi∼B(20,0.1)T=\sum\limits_{i=1}^{20}X_i\sim B(20,0.1), with parameter np=20×0.1=2np=20\times0.1=2.
  2. Approximate by the Poisson distribution with parameter 2: P{T=k}≈2kk!e−2P\{T=k\}\approx\dfrac{2^k}{k!}e^{-2}.
  3. Hence P{T≤1}=P{T=0}+P{T=1}≈200!e−2+211!e−2=e−2+2e−2=3e−2P\{T\le1\}=P\{T=0\}+P\{T=1\}\approx\dfrac{2^0}{0!}e^{-2}+\dfrac{2^1}{1!}e^{-2}=e^{-2}+2e^{-2}=3e^{-2}.
  4. Hence (C) is the correct choice.

Answer:

C

10. Let X1,X2,⋯ ,XnX_1,X_2,\cdots,X_n be a simple random sample from the normal population N(μ,2)N(\mu,2). Denote X‾=1n∑i=1nXi\overline{X}=\frac{1}{n}\sum\limits_{i=1}^n X_i, and let ZαZ_\alpha denote the upper α\alpha quantile of the standard normal distribution. The rejection region of the test of the hypothesis testing problem H0:μ≤1, H1:μ>1H_0:\mu\leq1,\ H_1:\mu>1 at significance level α\alpha is

A. {(X1,X2,⋯ ,Xn)∣X‾>1+2nZα}\left\{(X_1,X_2,\cdots,X_n)\mid \overline{X}>1+\frac{2}{n}Z_\alpha\right\}.

B. {(X1,X2,⋯ ,Xn)∣X‾>1+2nZα}\left\{(X_1,X_2,\cdots,X_n)\mid \overline{X}>1+\frac{\sqrt{2}}{n}Z_\alpha\right\}.

C. {(X1,X2,⋯ ,Xn)∣X‾>1+2nZα}\left\{(X_1,X_2,\cdots,X_n)\mid \overline{X}>1+\frac{2}{\sqrt{n}}Z_\alpha\right\}.

D. {(X1,X2,⋯ ,Xn)∣X‾>1+2nZα}\left\{(X_1,X_2,\cdots,X_n)\mid \overline{X}>1+\frac{\sqrt{2}}{\sqrt{n}}Z_\alpha\right\}.

mathematical statisticshypothesis testingnormal distributionrejection region

Approach:

This question tests the rejection region of a one-sided test for a normal population. The test statistic X‾−μσ/n\dfrac{\overline X-\mu}{\sigma/\sqrt n} follows the standard normal distribution, and substituting the boundary value of the null hypothesis gives the rejection region.

Steps:

  1. Since X1,…,XnX_1,\dots,X_n come from N(μ,2)N(\mu,2), we know that σ=2\sigma=\sqrt2, and X‾−μσ/n∼N(0,1)\dfrac{\overline X-\mu}{\sigma/\sqrt n}\sim N(0,1).
  2. For the one-sided test H0:μ≤1, H1:μ>1H_0:\mu\le1,\ H_1:\mu>1, the rejection region is X‾−12/n>Zα\dfrac{\overline X-1}{\sqrt2/\sqrt n}>Z_\alpha.
  3. Rearranging gives X‾>1+2nZα\overline X>1+\dfrac{\sqrt2}{\sqrt n}Z_\alpha.
  4. Hence (D) is the correct choice.

Answer:

D

Part II: Fill in the Blank

Part II: Fill in the Blank: Questions 11-16, 5 points each, 30 points in total.

11. lim⁡x→0+xx−1ln⁡x⋅ln⁡(1−x)=\lim\limits_{x\to0^+} \dfrac{x^x-1}{\ln x\cdot\ln(1-x)}=____.

limitL'Hopital's rulelogarithmic function

Approach:

This question tests the application of equivalent infinitesimals in the computation of a limit. Write xxx^x as exln⁡xe^{x\ln x} and then simplify with eu−1∼ue^u-1\sim u.

Steps:

  1. Since x→0+x\to0^+ implies ln⁡x→−∞\ln x\to-\infty and ln⁡(1−x)∼−x\ln(1-x)\sim-x, we have ln⁡x⋅ln⁡(1−x)∼−xln⁡x\ln x\cdot\ln(1-x)\sim-x\ln x.
  2. Also xx−1=exln⁡x−1∼xln⁡xx^x-1=e^{x\ln x}-1\sim x\ln x.
  3. Hence the original expression =lim⁡x→0+xln⁡x−xln⁡x=−1=\lim\limits_{x\to0^+}\dfrac{x\ln x}{-x\ln x}=-1.

Answer:

−1-1.

12. Given that the Fourier series of the function f(x)={0,0≤x<12x2,12≤x≤1f(x)=\begin{cases}0, & 0\leq x<\dfrac{1}{2} \\ x^2, & \dfrac{1}{2}\leq x\leq1\end{cases} is ∑n=1∞bnsin⁡nπx\sum\limits_{n=1}^{\infty} b_n\sin n\pi x, and S(x)S(x) is the sum function of ∑n=1∞bnsin⁡nπx\sum\limits_{n=1}^{\infty} b_n\sin n\pi x, then S(−72)=S\left(-\dfrac{7}{2}\right)=____.

Fourier seriessum functionperiodicity

Approach:

This question tests the periodicity of the sum function of a Fourier series. The Fourier series of ff, ∑bnsin⁡nπx\sum b_n\sin n\pi x, has period 2, so first the point is moved back into [0,1][0,1] by periodicity, and then the value is substituted.

Steps:

  1. The least positive period of sin⁡nπx\sin n\pi x is 2, so S(x)S(x) has period 2.
  2. Hence S(−72)=S(−72+4)=S(12)S\left(-\dfrac72\right)=S\left(-\dfrac72+4\right)=S\left(\dfrac12\right).
  3. Since x=12x=\dfrac12 is a point of continuity of ff, S(12)=f(12)=(12)2=18S\left(\dfrac12\right)=f\left(\dfrac12\right)=\left(\dfrac12\right)^2=\dfrac18.

Answer:

18\dfrac{1}{8}.

13. Given the function u(x,y,z)=xy2z3u(x,y,z)=xy^2z^3 and the vector n=(2,2,−1)\mathbf{n}=(2,2,-1), then ∂u∂n∣(1,1,1)=\left.\dfrac{\partial u}{\partial \mathbf{n}}\right|_{(1,1,1)}=____.

partial derivativedirectional derivativevectormultivariable function

Approach:

This question tests the computation of a directional derivative. The directional derivative is the inner product of the gradient with the unit vector in that direction.

Steps:

  1. The partial derivatives are ∂u∂x=y2z3\dfrac{\partial u}{\partial x}=y^2z^3, ∂u∂y=2xyz3\dfrac{\partial u}{\partial y}=2xyz^3, ∂u∂z=3xy2z2\dfrac{\partial u}{\partial z}=3xy^2z^2.
  2. The gradient at (1,1,1)(1,1,1) is (1,2,3)(1,2,3).
  3. The length of the direction vector n=(2,2,−1)\bm n=(2,2,-1) is 4+4+1=3\sqrt{4+4+1}=3, and its unit vector is n0=(23,23,−13)\bm n_0=\left(\dfrac23,\dfrac23,-\dfrac13\right).
  4. The directional derivative ∂u∂n∣(1,1,1)=(1,2,3)⋅(23,23,−13)=23+43−1=1\left.\dfrac{\partial u}{\partial\bm n}\right|_{(1,1,1)}=(1,2,3)\cdot\left(\dfrac23,\dfrac23,-\dfrac13\right)=\dfrac23+\dfrac43-1=1.

Answer:

11.

14. Let the oriented curve LL be the part of the parabola y=1−x2y=1-x^2 from the point (1,0)(1,0) to the point (−1,0)(-1,0). Then the line integral ∫L(y+cos⁡x)dx+(2x+cos⁡y)dy=\int_L (y+\cos x)dx+(2x+\cos y)dy=____.

line integralGreen's formuladouble integraltrigonometric function

Approach:

This question tests a second-kind line integral together with Green’s formula. The curve LL is not closed, so a straight segment is added to close it, and then Green’s formula turns the integral into a double integral.

Steps:

  1. Put P=y+cos⁡xP=y+\cos x, Q=2x+cos⁡yQ=2x+\cos y, then ∂Q∂x−∂P∂y=2−1=1\dfrac{\partial Q}{\partial x}-\dfrac{\partial P}{\partial y}=2-1=1.
  2. Let L0L_0 be the straight segment from (−1,0)(-1,0) to (1,0)(1,0); then LL and L0L_0 enclose the region D={x2+y2≤1, y≥0}D=\{x^2+y^2\le1,\ y\ge0\}.
  3. By Green’s formula, the integral along the closed circuit formed by L0L_0 and LL is I1=∬D(∂Q∂x−∂P∂y)dσ=∬D1 dσ=∫−11(1−x2)dx=43I_1=\iint_D\left(\dfrac{\partial Q}{\partial x}-\dfrac{\partial P}{\partial y}\right)d\sigma=\iint_D1\,d\sigma=\int_{-1}^1(1-x^2)dx=\dfrac43.
  4. The integral along L0L_0 is I2=∫−11cos⁡x dx=2sin⁡1I_2=\int_{-1}^1\cos x\,dx=2\sin1 (here y=0, dy=0y=0,\ dy=0).
  5. Since L0L_0 and LL have opposite directions, I=I1−I2=43−2sin⁡1I=I_1-I_2=\dfrac43-2\sin1.

Answer:

43−2sin⁡1\dfrac{4}{3}-2\sin1.

15. Let the matrix A=(42−3a3−4b5−7)A=\begin{pmatrix}4 & 2 & -3 \\ a & 3 & -4 \\ b & 5 & -7\end{pmatrix}. If the systems of equations A2x=0A^2x=0 and Ax=0Ax=0 do not have the same solutions, then a−b=a-b=____.

matrixdeterminantsystem of linear equationsmatrix rank

Approach:

This question tests the relation between a power of a matrix and the solutions of a system of equations. The fact that A2x=0A^2x=0 and Ax=0Ax=0 do not have the same solutions means that AA is not invertible, so the parameters can be determined from the vanishing of the determinant.

Steps:

  1. If AA were invertible, then A2x=0  ⟺  Ax=0A^2x=0\iff Ax=0, and the two would have the same solutions, contradicting the statement; hence AA is not invertible, that is ∣A∣=0|A|=0.
  2. Compute the determinant (expanding with respect to the doubling property of the second and the third column): ∣A∣=4∣0−11−2∣−(a−b)∣1−11−2∣|A|=4\begin{vmatrix}0&-1\\1&-2\end{vmatrix}-(a-b)\begin{vmatrix}1&-1\\1&-2\end{vmatrix}.
  3. Here ∣0−11−2∣=1\begin{vmatrix}0&-1\\1&-2\end{vmatrix}=1 and ∣1−11−2∣=−1\begin{vmatrix}1&-1\\1&-2\end{vmatrix}=-1, so ∣A∣=4−(a−b)⋅(−1)=4+a−b|A|=4-(a-b)\cdot(-1)=4+a-b.
  4. Setting ∣A∣=0|A|=0 gives a−b=−4a-b=-4.

Answer:

−4-4.

16. Let A,BA,B be two random events, with AA and BB mutually independent. Given P(A)=2P(B),P(A∪B)=58P(A)=2P(B),P(A\cup B)=\dfrac{5}{8}, then, under the condition that at least one of the events A,BA,B occurs, the probability that exactly one of A,BA,B occurs is____.

probability theoryconditional probabilityindependence of eventsprobability calculation

Approach:

This question tests the probability calculation for independent events and the conditional probability. First use independence to turn the probability of the union into an equation in P(B)P(B), solve for P(A),P(B)P(A),P(B), and then compute the conditional probability.

Steps:

  1. Put p=P(B)p=P(B), then P(A)=2pP(A)=2p, and by independence P(AB)=P(A)P(B)=2p2P(AB)=P(A)P(B)=2p^2.
  2. From P(A∪B)=P(A)+P(B)−P(AB)=58P(A\cup B)=P(A)+P(B)-P(AB)=\dfrac58 we get 3p−2p2=583p-2p^2=\dfrac58, that is 16p2−24p+5=016p^2-24p+5=0, that is (4p−1)(4p−5)=0(4p-1)(4p-5)=0.
  3. Take p=14p=\dfrac14 (the value p=54>1p=\dfrac54>1 is discarded), which gives P(B)=14, P(A)=12P(B)=\dfrac14,\ P(A)=\dfrac12.
  4. Hence the probability that “exactly one occurs” is P(AB‾)+P(A‾B)=P(A)+P(B)−2P(A)P(B)=12+14−2⋅12⋅14=12P(A\overline B)+P(\overline AB)=P(A)+P(B)-2P(A)P(B)=\dfrac12+\dfrac14-2\cdot\dfrac12\cdot\dfrac14=\dfrac12.
  5. Under the condition that A∪BA\cup B occurs, the required conditional probability is 1/25/8=45\dfrac{1/2}{5/8}=\dfrac45.

Answer:

45\dfrac{4}{5}.

Part III: Free Response

Part III: Free Response: Questions 17-22, 70 points in total. The solutions should include verbal explanations, proof procedures or computational steps.

17. (10 points)

Compute ∫011(x+1)(x2−2x+2)dx\int_0^1 \dfrac{1}{(x+1)(x^2-2x+2)}dx.

integralintegral of a rational functionpartial fraction decompositioninverse trigonometric function

Approach:

This question tests the indefinite integral of a rational function. First make a partial fraction decomposition and then integrate term by term, where the quadratic factor is turned into an arctangent after completing the square.

Steps:

  1. Make the partial fraction decomposition: 1(x+1)(x2−2x+2)=Ax+1+Bx+Cx2−2x+2\dfrac{1}{(x+1)(x^2-2x+2)}=\dfrac{A}{x+1}+\dfrac{Bx+C}{x^2-2x+2}; comparing coefficients gives A=15, B=−13, C=35A=\dfrac15,\ B=-\dfrac13,\ C=\dfrac35.
  2. Hence the original integral =∫01(15(x+1)+−13x+35x2−2x+2)dx=\displaystyle\int_0^1\left(\dfrac{1}{5(x+1)}+\dfrac{-\frac13x+\frac35}{x^2-2x+2}\right)dx.
  3. Here −13x+35x2−2x+2=−16⋅2x−2x2−2x+2+35⋅1(x−1)2+1\dfrac{-\frac13x+\frac35}{x^2-2x+2}=-\dfrac16\cdot\dfrac{2x-2}{x^2-2x+2}+\dfrac{3}{5}\cdot\dfrac{1}{(x-1)^2+1}.
  4. Integrate term by term: 15ln⁡2+110ln⁡22+35[arctan⁡(x−1)]01=15ln⁡2+35⋅π4\dfrac15\ln2+\dfrac{1}{10}\ln\dfrac{2}{2}+\dfrac35\left[\arctan(x-1)\right]_0^1=\dfrac15\ln2+\dfrac35\cdot\dfrac{\pi}{4}.
  5. That is, the original integral =310ln⁡2+110π=\dfrac{3}{10}\ln2+\dfrac{1}{10}\pi.

Answer:

310ln⁡2+110π\dfrac{3}{10}\ln 2+\dfrac{1}{10}\pi.

18. (10 points)

Given that the function f(u)f(u) has a second derivative on the interval (0,+∞)(0,+\infty), and putting g(x,y)=f(xy)g(x,y)=f\left(\dfrac{x}{y}\right), if g(x,y)g(x,y) satisfies

x2∂2g∂x2+xy∂2g∂x∂y+y2∂2g∂y2=1,x^2\frac{\partial^2 g}{\partial x^2}+xy\frac{\partial^2 g}{\partial x\partial y}+y^2\frac{\partial^2 g}{\partial y^2}=1,

and g(x,x)=1, ∂g∂x∣(x,x)=2xg(x,x)=1,\ \left.\frac{\partial g}{\partial x}\right|_{(x,x)}=\frac{2}{x}, find f(u)f(u).

partial differential equationmultivariable functionderivative of a composite functiondifferential equation

Approach:

This question tests the partial derivatives of a composite function of several variables and an ordinary differential equation with a parameter. First use the chain rule to express all the partial derivatives of gg in terms of f′f' and f′′f'', substitute them into the original equation to obtain an ordinary differential equation in uu, and finally use the initial values to determine the constant.

Steps:

  1. Put u=xyu=\dfrac{x}{y}, then ∂g∂x=f′(u)1y\dfrac{\partial g}{\partial x}=f'(u)\dfrac1y and ∂g∂y=f′(u)(−xy2)\dfrac{\partial g}{\partial y}=f'(u)\left(-\dfrac{x}{y^2}\right).
  2. From g(x,x)=f(1)=1g(x,x)=f(1)=1 and ∂g∂x∣(x,x)=f′(1)1x=2x\left.\dfrac{\partial g}{\partial x}\right|_{(x,x)}=f'(1)\dfrac1x=\dfrac2x we get f′(1)=2f'(1)=2.
  3. Compute the second partial derivatives: ∂2g∂x2=f′′(u)1y2\dfrac{\partial^2g}{\partial x^2}=f''(u)\dfrac1{y^2}, ∂2g∂x∂y=−xy3f′′(u)−1y2f′(u)\dfrac{\partial^2g}{\partial x\partial y}=-\dfrac{x}{y^3}f''(u)-\dfrac1{y^2}f'(u), ∂2g∂y2=x2y4f′′(u)+2xy3f′(u)\dfrac{\partial^2g}{\partial y^2}=\dfrac{x^2}{y^4}f''(u)+\dfrac{2x}{y^3}f'(u).
  4. Substituting the above into the original equation and simplifying gives u2f′′(u)+uf′(u)+1u2f′(u)=1u2u^2f''(u)+uf'(u)+\dfrac1{u^2}f'(u)=\dfrac1{u^2}.
  5. Put p=f′(u)p=f'(u), then u2p′′+up′+1u2p′=1u2u^2p''+up'+\dfrac1{u^2}p'=\dfrac1{u^2}, which gives p=ln⁡uu+2up=\dfrac{\ln u}{u}+\dfrac2u.
  6. Hence f′(u)=ln⁡uu+2uf'(u)=\dfrac{\ln u}{u}+\dfrac2u, and integrating gives f(u)=12ln⁡2u+2ln⁡u+Cf(u)=\dfrac12\ln^2u+2\ln u+C; since f(1)=1f(1)=1 we get C=1C=1.

Answer:

f(u)=12ln⁡2u+2ln⁡u+1f(u)=\dfrac{1}{2}\ln^{2}u+2\ln u+1.

19. (10 points)

Let the function f(x)f(x) be differentiable on the interval (a,b)(a,b). Prove that the derivative f′(x)f'(x) is strictly increasing on (a,b)(a,b) if and only if the following holds for the interval (a,b)(a,b): for arbitrary x1,x2,x3x_1,x_2,x_3 in it, when x1<x2<x3x_1<x_2<x_3,

f(x2)−f(x1)x2−x1<f(x3)−f(x1)x3−x1<f(x3)−f(x2)x3−x2\frac{f(x_2)-f(x_1)}{x_2-x_1}<\frac{f(x_3)-f(x_1)}{x_3-x_1}<\frac{f(x_3)-f(x_2)}{x_3-x_2}
derivativemonotonicityLagrange mean value theoremproof of a necessary and sufficient condition

Approach:

This question asks for the proof of a necessary and sufficient condition concerning the order of the slopes of secants. For sufficiency the monotonicity of f′f' is squeezed out of the limit of the secant slopes (that is, the left and right derivatives); for necessity the Lagrange mean value theorem is used directly.

Steps:

Solution:

Sufficiency: suppose that in (a,b)(a,b), for arbitrary x1,x2,x3x_1,x_2,x_3, when x1<x2<x3x_1<x_2<x_3, we always have

f(x2)−f(x1)x2−x1<f(x3)−f(x1)x3−x1<f(x3)−f(x2)x3−x2\frac{f(x_2)-f(x_1)}{x_2-x_1}<\frac{f(x_3)-f(x_1)}{x_3-x_1}<\frac{f(x_3)-f(x_2)}{x_3-x_2}

then, taking in (a,b)(a,b) arbitrary x1<x2<x3<x4<x5x_1<x_2<x_3<x_4<x_5, we have

f(x2)−f(x1)x2−x1<f(x3)−f(x2)x3−x2<f(x4)−f(x3)x4−x3<f(x5)−f(x4)x5−x4\frac{f(x_2)-f(x_1)}{x_2-x_1}<\frac{f(x_3)-f(x_2)}{x_3-x_2}<\frac{f(x_4)-f(x_3)}{x_4-x_3}<\frac{f(x_5)-f(x_4)}{x_5-x_4}

Letting both sides of f(x2)−f(x1)x2−x1<f(x3)−f(x2)x3−x2\frac{f(x_2)-f(x_1)}{x_2-x_1}<\frac{f(x_3)-f(x_2)}{x_3-x_2} tend to x2→x1+x_2\to x_1^+ gives

f+′(x1)≤f(x3)−f(x1)x3−x1f'_+(x_1)\leq\frac{f(x_3)-f(x_1)}{x_3-x_1}

and letting x2→x3−x_2\to x_3^- on both sides gives

f(x3)−f(x1)x3−x1≤f−′(x3)\frac{f(x_3)-f(x_1)}{x_3-x_1}\leq f'_-(x_3)

that is,

f+′(x1)≤f(x3)−f(x1)x3−x1≤f−′(x3)f'_+(x_1)\leq\frac{f(x_3)-f(x_1)}{x_3-x_1}\leq f'_-(x_3)

Similarly we get f+′(x3)≤f−′(x5)f'_+(x_3)\leq f'_-(x_5). Since

f(x3)−f(x1)x3−x1<f(x5)−f(x3)x5−x3\frac{f(x_3)-f(x_1)}{x_3-x_1}<\frac{f(x_5)-f(x_3)}{x_5-x_3}

it follows that f+′(x1)≤f−′(x5)f'_+(x_1)\leq f'_-(x_5). By the arbitrariness of x1,x5x_1,x_5, we get that f′(x)f'(x) is strictly increasing on (a,b)(a,b), and the sufficiency is proved.

Now prove the necessity, that is, assume that f′(x)f'(x) is monotonically increasing. Applying the Lagrange mean value theorem separately on [x1,x2],[x2,x3][x_1,x_2],[x_2,x_3], we know that there exist ξ1∈(x1,x2),ξ2∈(x2,x3)\xi_1\in(x_1,x_2),\xi_2\in(x_2,x_3) such that

f′(ξ1)=f(x2)−f(x1)x2−x1,f′(ξ2)=f(x3)−f(x2)x3−x2f'(\xi_1)=\frac{f(x_2)-f(x_1)}{x_2-x_1},\quad f'(\xi_2)=\frac{f(x_3)-f(x_2)}{x_3-x_2}

Since f′(x)f'(x) is monotonically increasing and ξ1<ξ2\xi_1<\xi_2, we know that f′(ξ1)<f′(ξ2)f'(\xi_1)<f'(\xi_2), that is,

f(x2)−f(x1)x2−x1<f(x3)−f(x2)x3−x2\frac{f(x_2)-f(x_1)}{x_2-x_1}<\frac{f(x_3)-f(x_2)}{x_3-x_2}

and the necessity is proved.

In summary, the necessary and sufficient condition is proved.

Answer:

The necessary and sufficient condition holds: for the interval (a,b)(a,b) and arbitrary x1<x2<x3x_1<x_2<x_3 in it, the inequality f(x2)−f(x1)x2−x1<f(x3)−f(x1)x3−x1<f(x3)−f(x2)x3−x2\dfrac{f(x_2)-f(x_1)}{x_2-x_1}<\dfrac{f(x_3)-f(x_1)}{x_3-x_1}<\dfrac{f(x_3)-f(x_2)}{x_3-x_2} holds if and only if f′(x)f'(x) is strictly increasing on (a,b)(a,b).

20. (10 points)

Let Σ\Sigma be the surface obtained by rotating the straight line {x=0,y=0\begin{cases}x=0,\\y=0\end{cases} once around the straight line {y=t,z=t\begin{cases}y=t,\\z=t\end{cases} (tt is the parameter), and let Σ1\Sigma_1 be the outer side of the part of Σ\Sigma lying between the plane x+y+z=0x+y+z=0 and the plane x+y+z=1x+y+z=1. Compute the surface integral

I=∬Σ1x dy dz+(y+1)dz dx+(z+2)dx dyI=\iint_{\Sigma_1} x\,dy\,dz+(y+1)dz\,dx+(z+2)dx\,dy
surface integralGauss's formulasurface of revolutiontriple integral

Approach:

This question tests the application of Gauss’s formula. The surface Σ1\Sigma_1 is the part of a surface of revolution cut off by two planes, so it is not closed; the plane Σ0:x+y+z=1\Sigma_0:x+y+z=1 is added to complete a closed surface, Gauss’s formula turns the integral into a triple integral, and the contribution of the added face is subtracted.

Steps:

Solution:

From the statement, the straight line {x=t,y=0,z=t\begin{cases}x=t,\\y=0,\\z=t\end{cases} is denoted by l1l_1 and the straight line {x=t,y=t,z=t\begin{cases}x=t,\\y=t,\\z=t\end{cases} is denoted by l2l_2; then the line l1l_1 rotating around the line l2l_2 gives the surface Σ\Sigma, which is (x−t)2+(y−t)2+(z−t)2=3t2(x-t)^2+(y-t)^2+(z-t)^2=3t^2.

It is known that Σ1\Sigma_1 is the outer side of Σ\Sigma lying between the plane x+y+z=0x+y+z=0 and x+y+z=1x+y+z=1, so the added face is Σ0:x+y+z=1\Sigma_0:x+y+z=1, with the direction pointing outwards. Then Σ0\Sigma_0 and Σ1\Sigma_1 enclose a closed region, and by Gauss’s formula,

I1=∬Σ0+Σ1x dy dz+(y+1)dz dx+(z+2)dx dy=∭Ω(1+1+1)dv=3∭Ωdv=3⋅13(22)224πI_1=\iint_{\Sigma_0+\Sigma_1} x\,dy\,dz+(y+1)dz\,dx+(z+2)dx\,dy=\iiint_{\Omega}(1+1+1)dv=3\iiint_{\Omega}dv=3\cdot\frac{1}{3}\left(\frac{\sqrt{2}}{2}\right)^2\frac{\sqrt{2}}{4}\pi

(Note: Ω\Omega is a cone).

Let DxyD_{xy} be the projection of Σ0\Sigma_0 on the xoyxoy plane, Dxy={(x,y)∣0≤x+y≤1,x≥0,y≥0}D_{xy}=\{(x,y)|0\leq x+y\leq 1,x\geq 0,y\geq 0\}

Also,

I2=∬Σ0x dy dz+(y+1)dz dx+(z+2)dx dy=∬Dxyx dy dz+(y+1)dz dx+(3−x−y)dx dyI_2=\iint_{\Sigma_0} x\,dy\,dz+(y+1)dz\,dx+(z+2)dx\,dy=\iint_{D_{xy}} x\,dy\,dz+(y+1)dz\,dx+(3-x-y)dx\,dy

=∬Dxy2dxdy=2⋅12⋅1⋅1=1=\iint_{D_{xy}} 2dxdy=2\cdot\frac{1}{2}\cdot1\cdot1=1

Hence I=I1−I2=24π−1I=I_1-I_2=\frac{\sqrt{2}}{4}\pi-1.

Answer:

I=24π−1I=\dfrac{\sqrt{2}}{4}\pi-1.

21. (10 points)

Let the matrix A=(0−12−102−1−1a)A=\begin{pmatrix}0 & -1 & 2 \\ -1 & 0 & 2 \\ -1 & -1 & a\end{pmatrix}, and given that 1 is a multiple root of the characteristic polynomial of AA.

(1) Find the value of aa;

(2) Find all nonzero column vectors satisfying Aα=α+β,A2α=α+2βA\alpha=\alpha+\beta, A^2\alpha=\alpha+2\beta, that is, all pairs α,β\alpha,\beta.

matrixeigenvaluecharacteristic polynomiallinear algebra

Approach:

This question tests the characteristic polynomial of a matrix and a linear algebra computation starting from an eigenvector. First determine the parameter from the constant term of the characteristic polynomial, and then use (A−E)2α=0(A-E)^2\alpha=0 to describe the relation between α,β\alpha,\beta.

Steps:

  1. (1) Compute the characteristic polynomial f(λ)=∣A−λE∣=(1−λ)[(λ−a)(λ+1)+4]f(\lambda)=|A-\lambda E|=(1-\lambda)\bigl[(\lambda-a)(\lambda+1)+4\bigr].
  2. From f(1)=0f(1)=0 we get (1−a)⋅2+4=0(1-a)\cdot2+4=0, which gives a=3a=3.
  3. (2) At this point A=(0−12−102−1−13)A=\begin{pmatrix}0&-1&2\\-1&0&2\\-1&-1&3\end{pmatrix}, whose eigenvalues are λ1=λ2=λ3=1\lambda_1=\lambda_2=\lambda_3=1.
  4. From Aα=α+βA\alpha=\alpha+\beta and A2α=α+2βA^2\alpha=\alpha+2\beta we get (A−E)α=β(A-E)\alpha=\beta and (A−E)2α=2β=2(A−E)α(A-E)^2\alpha=2\beta=2(A-E)\alpha, that is (A−E)2α=0(A-E)^2\alpha=0.
  5. Since (A−E)2≠0(A-E)^2\ne0, α\alpha may be any nonzero column vector α=(a1,a2,a3)T\alpha=(a_1,a_2,a_3)^T, where a1a2a3≠0a_1a_2a_3\ne0.
  6. At this point β=(A−E)α=(2a3−a1−a22a3−a1−a22a3−a1−a2)\beta=(A-E)\alpha=\begin{pmatrix}2a_3-a_1-a_2\\2a_3-a_1-a_2\\2a_3-a_1-a_2\end{pmatrix}, and it is required that a1+a2≠2a3a_1+a_2\ne2a_3 (otherwise β=0\beta=0, which contradicts the statement).

Answer:

(1) a=3a=3;

(2) α=(a1,a2,a3)T\alpha=(a_1,a_2,a_3)^T is an arbitrary nonzero column vector (a1a2a3≠0a_1a_2a_3\ne0), β=(2a3−a1−a2)(1,1,1)T\beta=(2a_3-a_1-a_2)(1,1,1)^T, and a1+a2≠2a3a_1+a_2\ne2a_3.

22. (12 points)

When the loss event of the policyholder occurs, the relation between the compensation amount YY paid by the insurance company and the loss amount XX of the policyholder is

Y={0,X≤100,x−100,X>100Y=\begin{cases}0, & X\leq 100,\\x-100, & X>100\end{cases}

Given that when the loss event occurs, the probability density of the loss amount XX of the policyholder is

f(x)={2×1002(100+x)3,x>0,0,x≤0f(x)=\begin{cases}\dfrac{2\times 100^2}{(100+x)^3}, & x>0,\\0, & x\leq 0\end{cases}

(1) Find P{Y>0}P\{Y>0\} and EYEY.

(2) Let the number of occurrences of this kind of loss event in one year be denoted by NN, and let the number of claims handled by the insurance company for this kind of loss event in one year be denoted by MM. Suppose that NN follows a Poisson distribution with parameter 8, and that under the condition N=n (n≥1)N=n\ (n\geq1), MM follows the binomial distribution B(n,p)B(n,p), where p=P{Y>0}p=P\{Y>0\}. Find the probability distribution of MM.

probability densityexpectationPoisson distributionbinomial distribution

Approach:

This question tests the computation of a probability and an expectation from a probability density, and the mixture of a Poisson distribution with a binomial distribution. The compensation amount YY is nonzero only when the loss exceeds 100, so first P{Y>0}P\{Y>0\} and EYEY are computed from the density; then the distribution of MM is written as a sum over NN by the law of total probability, and finally the expansion of the Poisson distribution turns it into a Poisson distribution.

Steps:

Solution:

(1)

P{Y>0}=P{X−100>0}=P{X>100}=∫100+∞2×1002(100+x)3dx=14P\{Y>0\}=P\{X-100>0\}=P\{X>100\}=\int_{100}^{+\infty}\dfrac{2\times 100^2}{(100+x)^3}dx=\dfrac{1}{4}EY=∫100+∞(x−100)2×1002(100+x)3dx=50EY=\int_{100}^{+\infty}(x-100)\dfrac{2\times 100^2}{(100+x)^3}dx=50

(2)

N∼P(8), {M∣N=n}∼B(n,14)N\sim P(8),\ \{M|N=n\}\sim B\left(n,\dfrac{1}{4}\right)P{M=m}=∑n=m∞P{N=n}⋅P{M=m∣N=n}P\{M=m\}=\sum_{n=m}^{\infty}P\{N=n\}\cdot P\{M=m|N=n\}=∑n=m∞8nn!e−8⋅Cnm(14)m(34)n−m=\sum_{n=m}^{\infty}\dfrac{8^n}{n!}e^{-8}\cdot C_n^m\left(\dfrac{1}{4}\right)^m\left(\dfrac{3}{4}\right)^{n-m}=∑n=m∞8nm!(n−m)!e−8(14)m(34)n−m=\sum_{n=m}^{\infty}\dfrac{8^n}{m!(n-m)!}e^{-8}\left(\dfrac{1}{4}\right)^m\left(\dfrac{3}{4}\right)^{n-m}=14me−88mm!∑n=m∞(6)n−m(n−m)!=\dfrac{1}{4^m}e^{-8}\dfrac{8^m}{m!}\sum_{n=m}^{\infty}\dfrac{(6)^{n-m}}{(n-m)!}=14me−88mm!e6=2mm!e−2=\dfrac{1}{4^m}e^{-8}\dfrac{8^m}{m!}e^6=\dfrac{2^m}{m!}e^{-2}

Answer:

(1) P{Y>0}=14P\{Y>0\}=\dfrac14, EY=50EY=50;

(2) MM follows a Poisson distribution with parameter 2, that is P{M=m}=2mm!e−2 (m=0,1,2,⋯ )P\{M=m\}=\dfrac{2^m}{m!}e^{-2}\ (m=0,1,2,\cdots).

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