2024 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 best fits the requirement of the question.

1. Given the functions f(x)=∫0xecos⁡tdt, g(x)=∫0sin⁡xet2dtf(x)=\int_0^x e^{\cos t}dt,\ g(x)=\int_0^{\sin x} e^{t^2}dt, then

(A) f(x)f(x) is an odd function and g(x)g(x) is an even function

(B) f(x)f(x) is an even function and g(x)g(x) is an odd function

(C) f(x)f(x) and g(x)g(x) are both odd functions

(D) f(x)f(x) and g(x)g(x) are both periodic functions

parity of a functionintegral functioncomposite function

Approach:

Analyse the parity of the functions and use the properties of integral functions.

Steps:

Since ecos⁡te^{\cos t} is an even function of tt, ∫0xecos⁡tdt\int_0^x e^{\cos t}dt is an odd function of xx, that is f(x)f(x) is odd. Put F(u)=∫0uet2dtF(u)=\int_0^u e^{t^2}dt; since et2e^{t^2} is an even function, F(u)F(u) is odd; and sin⁡x\sin x is odd, so g(x)=F(sin⁡x)g(x)=F(\sin x) is odd as well. Hence (C) is the correct choice.

Answer:

C

2. Let P=P(x,y,z),Q=Q(x,y,z)P=P(x,y,z),Q=Q(x,y,z) both be continuous functions, and let Σ\Sigma be the upper side of the surface z=1−x2−y2(x≤0,y≥0)z=\sqrt{1-x^2-y^2}(x\leq0,y\geq0). Then

∬ΣPdydz+Qdzdx=\iint_{\Sigma} Pdy dz+Qdz dx=

(A) ∬Σ(xzP+yzQ)dxdy\iint_{\Sigma} \left(\frac{x}{z}P+\frac{y}{z}Q\right)dxdy

(B) ∬Σ(−xzP+yzQ)dxdy\iint_{\Sigma} \left(-\frac{x}{z}P+\frac{y}{z}Q\right)dxdy

(C) ∬Σ(xzP−yzQ)dxdy\iint_{\Sigma} \left(\frac{x}{z}P-\frac{y}{z}Q\right)dxdy

(D) ∬Σ(−xzP−yzQ)dxdy\iint_{\Sigma} \left(-\frac{x}{z}P-\frac{y}{z}Q\right)dxdy

surface integralpartial derivativeintegral transformation

Approach:

Use the computation formula of the surface integral to turn the second-kind surface integral into a first-kind surface integral.

Steps:

Since ∂z∂x=−x1−x2−y2=−xz, ∂z∂y=−yz\frac{\partial z}{\partial x}=\frac{-x}{\sqrt{1-x^2-y^2}}=\frac{-x}{z},\ \frac{\partial z}{\partial y}=\frac{-y}{z}, we have ∬ΣPdydz+Qdzdx=∬ΣP⋅(−zx)+Q⋅(−zy)dxdy=∬Σ(xzP+yzQ)dxdy\iint_{\Sigma} Pdy dz+Qdz dx=\iint_{\Sigma} P\cdot(-z_x)+Q\cdot(-z_y)dxdy=\iint_{\Sigma} \left(\frac{x}{z}P+\frac{y}{z}Q\right)dxdy, so (A) is the correct choice.

Answer:

A

3. Given that the sum function of the power series ∑n=0∞anxn\sum\limits_{n=0}^{\infty} a_n x^n is ln⁡(2+x)\ln(2+x), then ∑n=0∞na2n=\sum\limits_{n=0}^{\infty} n a_{2n}=

(A) −16-\frac{1}{6}

(B) −13-\frac{1}{3}

(C) 16\frac{1}{6}

(D) 12\frac{1}{2}

power seriesTaylor expansionsummation of a series

Approach:

Use the Taylor expansion of the logarithmic function to find the coefficients of the power series.

Steps:

From ln⁡(1+x)=∑n=1∞(−1)n−1xnn,x∈(−1,1]\ln(1+x)=\sum\limits_{n=1}^{\infty}(-1)^{n-1}\frac{x^n}{n},x\in(-1,1] we get

ln⁡(2+x)=ln⁡2+ln⁡(1+x2)=ln⁡2+∑n=1∞(−1)n−11n(x2)n\ln(2+x)=\ln2+\ln(1+\frac{x}{2})=\ln2+\sum\limits_{n=1}^{\infty}(-1)^{n-1}\frac{1}{n}\left(\frac{x}{2}\right)^n

so an={ln⁡2,n=0,(−1)n−1n⋅2n,n≥1a_n=\begin{cases}\ln2, & n=0,\\ \frac{(-1)^{n-1}}{n\cdot2^n}, & n\geq1\end{cases}, and hence a2n=(−1)2n−12n⋅4n,n≥1a_{2n}=\frac{(-1)^{2n-1}}{2n\cdot4^n}, n\geq1.

∑n=0∞na2n=∑n=1∞na2n=∑n=1∞−12⋅4n=−12⋅14⋅11−14=−16\sum\limits_{n=0}^{\infty} n a_{2n}=\sum\limits_{n=1}^{\infty} n a_{2n}=\sum\limits_{n=1}^{\infty}\frac{-1}{2\cdot4^n}=-\frac{1}{2}\cdot\frac{1}{4}\cdot\frac{1}{1-\frac{1}{4}}=-\frac{1}{6}

Hence (A) is the correct choice.

Answer:

A

4. Let the function f(x)f(x) be defined on the interval (−1,1)(-1,1), and let lim⁡x→0f(x)=0\lim\limits_{x\to0} f(x)=0. Then

(A) When lim⁡x→0f(x)x=m\lim\limits_{x\to0} \dfrac{f(x)}{x}=m, we have f′(0)=mf'(0)=m

(B) When f′(0)=mf'(0)=m, we have lim⁡x→0f(x)x=m\lim\limits_{x\to0} \dfrac{f(x)}{x}=m

(C) When lim⁡x→0f′(x)=m\lim\limits_{x\to0} f'(x)=m, we have f′(0)=mf'(0)=m

(D) When f′(0)=mf'(0)=m, we have lim⁡x→0f′(x)=m\lim\limits_{x\to0} f'(x)=m

function limitderivativecounterexample construction

Approach:

Judge the correctness of each option by constructing counterexamples and by using the definition of the derivative.

Steps:

For option (A), take f(x)={mx,x≠01,x=0f(x)=\begin{cases}mx, & x\neq0 \\ 1, & x=0\end{cases}; then lim⁡x→0f(x)x=m\lim\limits_{x\to0} \dfrac{f(x)}{x}=m, but f(x)f(x) is not differentiable at x=0x=0, so (A) is excluded.

For option (B), since f′(0)=mf'(0)=m, the function f(x)f(x) is continuous at x=0x=0, so f(0)=lim⁡x→0f(x)=0f(0)=\lim\limits_{x\to0} f(x)=0, and hence lim⁡x→0f(x)x=lim⁡x→0f(x)−f(0)x=f′(0)=m\lim\limits_{x\to0} \dfrac{f(x)}{x}=\lim\limits_{x\to0} \dfrac{f(x)-f(0)}{x}=f'(0)=m, so (B) is correct.

For option (C), take f(x)={mx,x≠01,x=0f(x)=\begin{cases}mx, & x\neq0 \\ 1, & x=0\end{cases}; then lim⁡x→0f′(x)=m\lim\limits_{x\to0} f'(x)=m, but f(x)f(x) is not differentiable at x=0x=0, so (C) is excluded.

For option (D), take f(x)={mx+x2sin⁡1x,x≠00,x=0f(x)=\begin{cases}mx+x^2\sin\dfrac{1}{x}, & x\neq0 \\ 0, & x=0\end{cases}; then f′(0)=mf'(0)=m, but lim⁡x→0f′(x)\lim\limits_{x\to0} f'(x) does not exist, so (D) is excluded. Hence (B) is the correct choice.

Answer:

B

5. In the rectangular coordinate system O−xyzO-xyz in space, the relative position of the three planes πi:aix+biy+ciz=di(i=1,2,3)\pi_i: a_ix+b_iy+c_iz=d_i (i=1,2,3) is as shown in the figure included with the original paper (the original paper carries a diagram of the three planes; it is omitted in this transcription, so read the question against the original paper). Denote

αi=(α1α2α3), βi=(β1β2β3), if r=(α1α2α3)=m, r=(β1β2β3)=n, then\alpha_i=\begin{pmatrix}\alpha_1\\\alpha_2\\\alpha_3\end{pmatrix},\ \beta_i=\begin{pmatrix}\beta_1\\\beta_2\\\beta_3\end{pmatrix},\ \text{if}~r=\begin{pmatrix}\alpha_1\\\alpha_2\\\alpha_3\end{pmatrix}=m,\ r=\begin{pmatrix}\beta_1\\\beta_2\\\beta_3\end{pmatrix}=n,\ \text{then}

(A) m=1,n=2m=1,n=2

(B) m=n=2m=n=2

(C) m=2,n=3m=2,n=3

(D) m=n=3m=n=3

system of linear equationsmatrix rankplane geometry

Approach:

Analyse the relative position of the three planes and use the properties of the solutions of the system of linear equations.

Steps:

From the figure in the original paper, the three planes meet in a single straight line, so the system of equations

{a1x+b1y+c1z=d1,a2x+b2y+c2z=d2,a3x+b3y+c3z=d3\begin{cases} a_1x+b_1y+c_1z=d_1,\\ a_2x+b_2y+c_2z=d_2,\\ a_3x+b_3y+c_3z=d_3 \end{cases}

has infinitely many solutions, so r(α1α2α3)=r(β1β2β3)<3r\begin{pmatrix}\alpha_1\\\alpha_2\\\alpha_3\end{pmatrix}=r\begin{pmatrix}\beta_1\\\beta_2\\\beta_3\end{pmatrix}\lt3, that is m=n<3m=n<3. Moreover, the normal vectors of the three planes are coplanar, but those of π1\pi_1 and π2\pi_2 are not collinear, so r=2r=2 follows, hence m=n=2m=n=2, and (B) is the correct choice.

Answer:

B

6. Let the vectors α1=(a1−11), α2=(1ba1), α3=(1a−11)\alpha_1=\begin{pmatrix}a\\1\\-1\\1\end{pmatrix},\ \alpha_2=\begin{pmatrix}1\\b\\a\\1\end{pmatrix},\ \alpha_3=\begin{pmatrix}1\\a\\-1\\1\end{pmatrix}. If α1,α2,α3\alpha_1,\alpha_2,\alpha_3 are linearly dependent, and any two of them are linearly independent, then ( )

A. a=1,b≠−1a=1,b\neq-1

B. a=1,b=−1a=1,b=-1

C. a≠−2,b=2a\neq-2,b=2

D. a=−2,b=2a=-2,b=2

linear dependence of vectorsdeterminantmatrix rank

Approach:

Use the condition of linear dependence of vectors and solve for the parameters by means of determinants.

Steps:

Since α1,α2,α3\alpha_1,\alpha_2,\alpha_3 are linearly dependent, r(α1,α2,α3)<3r(\alpha_1,\alpha_2,\alpha_3)\lt3, so

∣a1111a1a1∣=0,\left|\begin{matrix}a & 1 & 1\\1 & 1 & a\\1 & a & 1\end{matrix}\right|=0,

which gives a=1a=1 or a=−2a=-2. When a=1a=1, α1,α3\alpha_1,\alpha_3 are linearly dependent, contradicting the statement, so a=−2a=-2.

Also, from

∣a1111a−1b−1∣=∣−21111−2−1b−1∣=0,\left|\begin{matrix}a & 1 & 1\\1 & 1 & a\\-1 & b & -1\end{matrix}\right|=\left|\begin{matrix}-2 & 1 & 1\\1 & 1 & -2\\-1 & b & -1\end{matrix}\right|=0,

we get b=2b=2, so D is the correct choice.

Answer:

D

7. Let AA be a matrix of order 3 with rank 2, and let α\alpha be a nonzero vector satisfying Aα=0A\alpha=0. If βTα=0\beta^T\alpha=0 holds for every 3-dimensional column vector β\beta, then Aβ=βA\beta=\beta holds for all of them, so ( )

A. The trace of A3A^3 is 2

B. The trace of A3A^3 is 5

C. The trace of A2A^2 is 8

D. The trace of A2A^2 is 9

eigenvalue of a matrixtrace of a matrixlinear algebra

Approach:

Analyse the eigenvalues and eigenvectors of the matrix and compute the trace of a power of the matrix.

Steps:

From Aα=0A\alpha=0 and α≠0\alpha\neq0 we get λ1=0\lambda_1=0. Take nonzero vectors β1,β2\beta_1,\beta_2 that are linearly independent (the plane perpendicular to α\alpha certainly contains two linearly independent vectors) and satisfy β1Tα=β2Tα=0\beta_1^T\alpha=\beta_2^T\alpha=0; then Aβ1=β1,Aβ2=β2A\beta_1=\beta_1,A\beta_2=\beta_2, and since β1,β2\beta_1,\beta_2 are linearly independent, λ=1\lambda=1 is at least a double root, so λ1=0,λ2=λ3=1\lambda_1=0,\lambda_2=\lambda_3=1. Hence the eigenvalues of A3A^3 are 0,1,10,1,1, so tr(A3)=0+1+1=2tr(A^3)=0+1+1=2, and A is the correct choice.

Answer:

A

8. Let the random variables X,YX,Y be mutually independent, with XX following the normal distribution N(0,2)N(0,2) and YY following the normal distribution N(−2,2)N(-2,2). If P{2X+Y<a}=P{X>Y}P\{2X+Y<a\}=P\{X>Y\}, then a=a=( )

A. −2−10-2-\sqrt{10}

B. −2+10-2+\sqrt{10}

C. −2−6-2-\sqrt{6}

D. −2+6-2+\sqrt{6}

normal distributionprobability calculationrandom variable

Approach:

Solve the problem using the properties of the normal distribution and the probability computation formula.

Steps:

2X+Y∼N(−2,10)2X+Y\sim N(-2,10), Y−X∼N(−2,22)Y-X\sim N(-2,2^2),

so P{2X+Y<a}=Φ(a+210)=P{Y−X<0}=Φ(0+22)P\{2X+Y<a\}=\Phi\left(\frac{a+2}{\sqrt{10}}\right)=P\{Y-X<0\}=\Phi\left(\frac{0+2}{2}\right).

Hence a+210=1⇒a=−2+10\frac{a+2}{\sqrt{10}}=1\Rightarrow a=-2+\sqrt{10}.

So B is the correct choice.

Answer:

B

9. Let the probability density of the random variable XX be f(x)={2(1−x),0<x<10,otherf(x)=\begin{cases}2(1-x), & 0<x<1 \\ 0, & \text{other}\end{cases}. Under the condition X=x(0<x<1)X=x(0<x<1), the random variable YY follows the uniform distribution on the interval (x,1)(x,1). Then Cov(X,Y)=\mathrm{Cov}(X,Y)=( )

A. −136-\dfrac{1}{36}

B. −172-\dfrac{1}{72}

C. 172\dfrac{1}{72}

D. 136\dfrac{1}{36}

conditional probability densitycovarianceintegral calculation

Approach:

Compute the covariance by means of the conditional probability density and the joint probability density.

Steps:

When 0<x<10<x<1, fY∣X(y∣x)={11−x,x<y<10,otherf_{Y|X}(y|x)=\begin{cases}\dfrac{1}{1-x}, & x<y<1 \\ 0, & \text{other}\end{cases}

f(x,y)={2,x<y<1,0<x<10,otherf(x,y)=\begin{cases}2, & x<y<1,0<x<1 \\ 0, & \text{other}\end{cases}

EXY=∬xyf(x,y)dxdy=∫01dy∫0y2xydx=14EXY=\iint xyf(x,y)dxdy=\int_0^1 dy\int_0^y 2xydx=\dfrac{1}{4}

EX=∫01x2(1−x)dx=13EX=\int_0^1 x2(1-x)dx=\dfrac{1}{3}

EY=∬yf(x,y)dxdy=∫01dy∫0y2ydx=23EY=\iint yf(x,y)dxdy=\int_0^1 dy\int_0^y 2ydx=\dfrac{2}{3}

Cov(X,Y)=EXY−EXEY=136\mathrm{Cov}(X,Y)=EXY-EXEY=\dfrac{1}{36}, so D is the correct choice.

Answer:

D

10. Let the random variables X,YX,Y be mutually independent, and let both follow an exponential distribution with parameter λ\lambda. Put Z=∣X−Y∣Z=|X-Y|. Then the random variable that has the same distribution as ZZ is ( )

A) X+YX+Y

B) X+Y2\dfrac{X+Y}{2}

C) 2X2X

D) XX

exponential distributiondistribution functionrandom variable

Approach:

Compute the distribution function of the random variable Z and judge the type of its distribution.

Steps:

The joint probability density of the random variables XX and YY is f(x,y)={λ2e−λ(x+y),x>0,y>00,otherf(x,y)=\begin{cases}\lambda^2 e^{-\lambda(x+y)}, & x>0,y>0 \\ 0, & \text{other}\end{cases}. The distribution function of the random variable ZZ is FZ(Z)=P(Z≤z)=P(∣X−Y∣≤z)F_Z(Z)=P(Z\leq z)=P(|X-Y|\leq z),

When z≤0z\leq0, FZ(Z)=0F_Z(Z)=0;

When z>0z>0,

FZ(Z)=P(−z<X−Y<z)=∫0zdu∫0u+zλ2e−λ(u+v)dv+∫z+∞du∫u−zu+zλ2e−λ(u+v)dvF_Z(Z)=P(-z<X-Y<z)=\int_0^z du\int_0^{u+z} \lambda^2 e^{-\lambda(u+v)}dv+\int_z^{+\infty} du\int_{u-z}^{u+z} \lambda^2 e^{-\lambda(u+v)}dv

=1−e−λz=1-e^{-\lambda z}

It is easy to see that the random variable ZZ follows an exponential distribution with parameter λ\lambda, so (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. Given lim⁡x→0(1+ax2)sin⁡x−1x3=6\lim\limits_{x\to0} \dfrac{(1+ax^2)^{\sin x}-1}{x^3}=6, then a=a=____.

limit calculationequivalent infinitesimalL'Hopital's rule

Answer:

6

Approach:

Compute by means of equivalent infinitesimals and the properties of limits.

Steps:

From the given condition,

6=lim⁡x→0(1+ax2)sin⁡x−1x3=lim⁡x→0esin⁡xln⁡(1+ax2)−1x3=lim⁡x→0sin⁡xln⁡(1+ax2)x3=lim⁡x→0x⋅ax2x3=a6=\lim_{x\to0} \dfrac{(1+ax^2)^{\sin x}-1}{x^3}=\lim_{x\to0} \dfrac{e^{\sin x\ln(1+ax^2)}-1}{x^3}=\lim_{x\to0} \dfrac{\sin x\ln(1+ax^2)}{x^3}=\lim_{x\to0} \dfrac{x\cdot ax^2}{x^3}=a

so a=6a=6.

12. Given that the second partial derivatives of f(u,v)f(u,v) exist and f(1,1)=3du+4vf(1,1)=3du+4v, if y=f(cos⁡x,1+x2)y=f(\cos x,1+x^2), then d2ydx2∣x=0=\left.\dfrac{d^2y}{dx^2}\right|_{x=0}=____.

derivative of a composite functionpartial derivativesecond derivative

Answer:

5

Approach:

Compute the second derivative by means of the differentiation rule for a composite function of several variables.

Steps:

Put u=cos⁡x,v=1+x2u=\cos x,v=1+x^2, then y=f(u,v)y=f(u,v), and by the differentiation rule for a composite function of several variables,

dydx=fu′(u,v)⋅(−sin⁡x)+fv′(u,v)⋅2x\frac{dy}{dx}=f'_u(u,v)\cdot(-\sin x)+f'_v(u,v)\cdot2xd2ydx2=−cos⁡x⋅fu′(u,v)−sin⁡x[fuu′′(u,v)⋅(−sin⁡x)+fuv′′(u,v)⋅2x]+fuv′′(u,v)⋅2x\frac{d^2y}{dx^2}=-\cos x\cdot f'_u(u,v)-\sin x\left[f''_{uu}(u,v)\cdot(-\sin x)+f''_{uv}(u,v)\cdot2x\right]+f''_{uv}(u,v)\cdot2x+2fv′(u,v)+2x[fvu′′(u,v)⋅(−sin⁡x)+fvv′′(u,v)⋅2x]+2f'_v(u,v)+2x\left[f''_{vu}(u,v)\cdot(-\sin x)+f''_{vv}(u,v)\cdot2x\right]

Hence

d2ydx2∣x=0=−fuu′′(1,1)+2fv′(1,1)=−3+2×4=5\left.\frac{d^2y}{dx^2}\right|_{x=0}=-f''_{uu}(1,1)+2f'_v(1,1)=-3+2\times4=5

13. Given f(x)=1+xf(x)=1+x, if f(x)=a02+∑n=1∞ancos⁡nx,x∈[0,π]f(x)=\dfrac{a_0}{2}+\sum\limits_{n=1}^{\infty} a_n\cos nx, x\in[0,\pi], then lim⁡n→∞n2sin⁡a2n−1=\lim\limits_{n\to\infty} n^2\sin a_{2n-1}=____.

Fourier seriescosine serieslimit calculation

Answer:

−1π-\frac{1}{\pi}

Approach:

Compute the coefficients of the Fourier cosine series and then find the limit.

Steps:

First make the even extension of the function f(x)f(x) and then its periodic extension,

an=2π∫0πf(x)cos⁡nxdx=2π∫0π(x+1)cos⁡nxdxa_n=\frac{2}{\pi}\int_0^{\pi} f(x)\cos nxdx=\frac{2}{\pi}\int_0^{\pi} (x+1)\cos nxdx=2nπ∫0π(x+1)d(sin⁡nx)=2nπ[(x+1)sin⁡nx∣0π−∫0πsin⁡nxdx]=\frac{2}{n\pi}\int_0^{\pi} (x+1)d(\sin nx)=\frac{2}{n\pi}\left[(x+1)\sin nx\Big|_0^{\pi}-\int_0^{\pi} \sin nx dx\right]=2n2π((−1)n−1)=\frac{2}{n^2\pi}((-1)^n-1)

Hence lim⁡n→∞n2sin⁡a2n−1=lim⁡n→∞−4(2n−1)2π=−1π\lim\limits_{n\to\infty} n^2\sin a_{2n-1}=\lim\limits_{n\to\infty} \frac{-4}{(2n-1)^2\pi}=-\frac{1}{\pi}.

14. The solution of the differential equation y′=1(x+y)2y' = \frac{1}{(x+y)^2} satisfying y(1)=0y(1)=0 is____.

differential equationsubstitutionseparation of variables

Answer:

x=tan⁡(y+π4)−yx=\tan\left(y+\frac{\pi}{4}\right)-y

Approach:

Turn the differential equation into a separable one by a substitution.

Steps:

Put u=x+yu=x+y, then dudx=1+y′\frac{du}{dx}=1+y', and substituting into the equation gives,

dudx=1+1u2, ⇒u2du=dx\frac{du}{dx}=1+\frac{1}{u^2},\ \Rightarrow u^2du=dx

After separating the variables, u2du=dxu^2du=dx, and integrating both sides gives u−arctan⁡u=x+Cu-\arctan u=x+C, so the general solution of the equation is y−arctan⁡(x+y)=Cy-\arctan(x+y)=C. Substituting the initial condition y(1)=0y(1)=0 gives C=π4C=\frac{\pi}{4}, so the particular solution required is y−arctan⁡(x+y)=π4y-\arctan(x+y)=\frac{\pi}{4}, that is x=tan⁡(y+π4)−yx=\tan\left(y+\frac{\pi}{4}\right)-y.

15. Given the matrix A=(a+1aaa)A=\begin{pmatrix}a+1 & a \\ a & a\end{pmatrix}, for arbitrary α=(x1x2),β=(y1y2)\alpha=\begin{pmatrix}x_1\\x_2\end{pmatrix},\beta=\begin{pmatrix}y_1\\y_2\end{pmatrix} we always have (αTAβαT−αβTAβ)2≤αTAα⋅βTAβ(\alpha^T A\beta\alpha^T-\alpha\beta^T A\beta)^2\leq \alpha^T A\alpha\cdot \beta^T A\beta, then the range of aa is____.

matrix inequalityquadratic formrange of the parameter

Answer:

a≥0a\geq0

Approach:

Analyse the matrix inequality and determine the range of the parameter.

Steps:

By the associativity of matrix multiplication,

αTA(βαT−αβT)Aβ≤0\alpha^T A(\beta\alpha^T-\alpha\beta^T)A\beta\leq0

From

βαT−αβT=(y1y2x1x2)−(x1x2y1y2)=(0−110)\beta\alpha^T-\alpha\beta^T=\begin{pmatrix}y_1 & y_2\\x_1 & x_2\end{pmatrix}-\begin{pmatrix}x_1 & x_2\\y_1 & y_2\end{pmatrix}=\begin{pmatrix}0 & -1\\1 & 0\end{pmatrix}

it follows that

A(βαT−αβT)A=(a+1aaa)(0−110)(a+1aaa)=a(x1y2−x2y1)(0−110)A(\beta\alpha^T-\alpha\beta^T)A=\begin{pmatrix}a+1 & a\\a & a\end{pmatrix}\begin{pmatrix}0 & -1\\1 & 0\end{pmatrix}\begin{pmatrix}a+1 & a\\a & a\end{pmatrix}=a(x_1y_2-x_2y_1)\begin{pmatrix}0 & -1\\1 & 0\end{pmatrix}

Hence αTA(βαT−αβT)Aβ=a(x1y2−x2y1)2\alpha^T A(\beta\alpha^T-\alpha\beta^T)A\beta=a(x_1y_2-x_2y_1)^2.

If αTA(βαT−αβT)Aβ≤0\alpha^T A(\beta\alpha^T-\alpha\beta^T)A\beta\leq0 always holds, that is if −a(x1y2−x2y1)2≤0-a(x_1y_2-x_2y_1)^2\leq0 always holds, then a≥0a\geq0.

16. Let the probability of success of the event AA each time be pp. In three independent repeated trials, under the condition that the event AA succeeds at least once, the probability that all three trials succeed is 413\dfrac{4}{13}. Then p=p=____.

conditional probabilityprobability calculationindependent events

Answer:

23\dfrac{2}{3}

Approach:

Solve for the probability parameter by means of the conditional probability formula.

Steps:

Let the event AA denote that the three experiments succeed at least once and the event BB denote that all three experiments succeed; then

P(A)=1−P(A‾)=1−(1−p)3, P(B)=p3, P(B∣A)=413P(A)=1-P(\overline{A})=1-(1-p)^3,\ P(B)=p^3,\ P(B|A)=\frac{4}{13}

By the conditional probability formula,

P(B∣A)=P(AB)P(A)=P(B)P(A)=p31−(1−p)3=413P(B|A)=\frac{P(AB)}{P(A)}=\frac{P(B)}{P(A)}=\frac{p^3}{1-(1-p)^3}=\frac{4}{13}

Solving gives p=23p=\dfrac{2}{3}.

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)

Let D={(x,y)∣1−y2≤x≤1,−1≤y≤1}D=\{(x,y)|\sqrt{1-y^2}\leq x\leq1,-1\leq y\leq1\}. Find ∬Dxx2+y2dxdy\iint_D \dfrac{x}{\sqrt{x^2+y^2}}dxdy.

double integralpolar coordinatesregion of integration

Answer:

2+ln⁡(1+2)−2\sqrt{2}+\ln(1+\sqrt{2})-2

Approach:

Use the symmetry of the region of integration and decompose the region of integration into simple subregions.

Steps:

Clearly the region of integration DD is symmetric about the xx-axis, so denote the part of DD above the xx-axis by D1D_1; then

∬Dxx2+y2dxdy=2∬D1xx2+y2dxdy\iint_D \frac{x}{\sqrt{x^2+y^2}}dxdy=2\iint_{D_1} \frac{x}{\sqrt{x^2+y^2}}dxdy

Denote D2={(x,y)∣0≤x≤1,0≤y≤1},D3={(x,y)∣x2+y2≤1,x≥0,y≥0}D_2=\{(x,y)|0\leq x\leq1,0\leq y\leq1\},D_3=\{(x,y)|x^2+y^2\leq1,x\geq0,y\geq0\}; then

∬D2xx2+y2dxdy=∫01dy∫01xx2+y2dx=∫01x2+y2∣x=0x=1dy\iint_{D_2} \frac{x}{\sqrt{x^2+y^2}}dxdy=\int_0^1 dy\int_0^1 \frac{x}{\sqrt{x^2+y^2}}dx=\int_0^1 \sqrt{x^2+y^2}\Big|_{x=0}^{x=1}dy=∫011+y2dy−∫01ydy=22+12ln⁡(1+2)−12=\int_0^1 \sqrt{1+y^2}dy-\int_0^1 ydy=\frac{\sqrt{2}}{2}+\frac{1}{2}\ln(1+\sqrt{2})-\frac{1}{2}∬D3xx2+y2dxdy=∫0π/2dθ∫01rcos⁡θdr=12\iint_{D_3} \frac{x}{\sqrt{x^2+y^2}}dxdy=\int_0^{\pi/2} d\theta\int_0^1 r\cos\theta dr=\frac{1}{2}

Hence

∬D1xx2+y2dxdy=∬D2xx2+y2dxdy−∬D3xx2+y2dxdy=22+12ln⁡(1+2)−1\iint_{D_1} \frac{x}{\sqrt{x^2+y^2}}dxdy=\iint_{D_2} \frac{x}{\sqrt{x^2+y^2}}dxdy-\iint_{D_3} \frac{x}{\sqrt{x^2+y^2}}dxdy=\frac{\sqrt{2}}{2}+\frac{1}{2}\ln(1+\sqrt{2})-1

Hence

∬Dxx2+y2dxdy=2+ln⁡(1+2)−2\iint_D \frac{x}{\sqrt{x^2+y^2}}dxdy=\sqrt{2}+\ln(1+\sqrt{2})-2

18. (12 points)

Let f(x,y)=x3+y3−(x+y)3+3f(x,y)=x^3+y^3-(x+y)^3+3. Given that the equation of the tangent plane to z=f(x,y)z=f(x,y) at (1,1,1)(1,1,1) is TT, and that TT together with the coordinate planes encloses a bounded region whose projection on the xoyxoy plane is DD.

(1) Find the equation of TT;

(2) Find the maximum and the minimum of f(x,y)f(x,y) on DD.

tangent planeextremum of a multivariable functionpartial derivative

Answer:

(1) x+y+z=3x+y+z=3

(2) the maximum value is 2121, and the minimum value is 1727\frac{17}{27}

Approach:

(1) Use the partial derivatives to find the equation of the tangent plane.

(2) Use the Lagrange multiplier method to find the extrema of a multivariable function.

Steps:

(1) From ∂z∂x∣(1,1,1)=[3x2−2(x+y)]∣(1,1,1)=1\frac{\partial z}{\partial x}|_{(1,1,1)}=[3x^2-2(x+y)]|_{(1,1,1)}=1, ∂z∂y∣(1,1,1)=[3y2−2(x+y)]∣(1,1,1)=−1\frac{\partial z}{\partial y}|_{(1,1,1)}=[3y^2-2(x+y)]|_{(1,1,1)}=-1, the normal vector to the tangent plane z=z(x,y)z=z(x,y) at (1,1,1)(1,1,1) is (−1,−1,−1)(-1,-1,-1), so the equation of the tangent plane TT is

−(x−1)−(y−1)−(z−1)=0, i.e. x+y+z=3-(x-1)-(y-1)-(z-1)=0,\ \text{i.e.}\ x+y+z=3

(2) From the statement, D={(x,y)∣x≥0,y≥0,x+y≤3}D=\{(x,y)|x\geq0,y\geq0,x+y\leq3\}. In the interior of the region DD, from

{∂z∂x=3x2−2(x+y)=0,∂z∂y=3y2−2(x+y)=0\begin{cases} \frac{\partial z}{\partial x}=3x^2-2(x+y)=0,\\ \frac{\partial z}{\partial y}=3y^2-2(x+y)=0 \end{cases}

the stationary points are (0,0),(43,43)(0,0),(\frac{4}{3},\frac{4}{3}), and it is easy to obtain f(0,0)=3,f(43,43)=1727f(0,0)=3,f(\frac{4}{3},\frac{4}{3})=\frac{17}{27}. In the region DD, on the boundary y=0,0≤x≤3y=0,0\leq x\leq3, we have f(x,0)=x3−x2+3f(x,0)=x^3-x^2+3, and from df(x,0)dx=3x2−2x=0\frac{df(x,0)}{dx}=3x^2-2x=0 the stationary points are x=0x=0 and x=23x=\frac{2}{3}, at which f(0,0)=3,f(23,0)=7727f(0,0)=3,f(\frac{2}{3},0)=\frac{77}{27}. Similarly, in the region DD, the stationary points on the boundary x=0,0≤y≤3x=0,0\leq y\leq3 are y=0,23y=0,\frac{2}{3}, and f(0,0)=3,f(0,23)=7727f(0,0)=3,f(0,\frac{2}{3})=\frac{77}{27}. In the region DD, on the boundary x+y=3,0≤x≤3x+y=3,0\leq x\leq3, we have f(x,3−x)=x3+(3−x)3−6x+3f(x,3-x)=x^3+(3-x)^3-6x+3; put φ(x)=x3+(3−x)3−6x+3\varphi(x)=x^3+(3-x)^3-6x+3, then φ′(x)=3x2−3(3−x)2−6=0\varphi'(x)=3x^2-3(3-x)^2-6=0 gives the stationary point x=32x=\frac{3}{2}, so the stationary point of the function f(x,y)f(x,y) on x+y=3x+y=3 is (32,32)(\frac{3}{2},\frac{3}{2}), at which f(32,32)=−34f(\frac{3}{2},\frac{3}{2})=-\frac{3}{4}. Moreover f(3,0)=f(0,3)=21f(3,0)=f(0,3)=21, and comparison shows that f(x,y)f(x,y) attains its maximum at the point (3,0)(3,0) or (0,3)(0,3), the maximum value being 2121, and attains its minimum at the point (43,43)(\frac{4}{3},\frac{4}{3}), the minimum value being 1727\frac{17}{27}.

19. (12 points)

Let the function f(x)f(x) have a second derivative, and let f′(0)=f′(1),∣f′′(x)∣≤1f'(0)=f'(1), |f''(x)|\leq1. Prove:

(1) When x∈(0,1)x\in(0,1), ∣f(x)−f(0)(1−x)−f(1)x∣≤x(1−x)2|f(x)-f(0)(1-x)-f(1)x|\leq\dfrac{x(1-x)}{2};

(2) ∣∫01f(x)dx−f(0)+f(1)2∣≤112\left|\int_0^1 f(x)dx-\dfrac{f(0)+f(1)}{2}\right|\leq\dfrac{1}{12}.

Taylor formulaintegral inequalityproperty of the derivative

Approach:

Prove the inequalities by means of the Taylor formula and the properties of integrals.

Steps:

(1) Expanding the function f(x)f(x) by the Taylor formula at x=0x=0 and at x=1x=1 gives,

f(x)=f(0)+f′(0)x+f′′(ξ1)2!x2, ξ1∈(0,x)f(x)=f(0)+f'(0)x+\frac{f''(\xi_1)}{2!}x^2,\ \xi_1\in(0,x)f(x)=f(1)+f′(1)(x−1)+f′′(ξ2)2!(x−1)2, ξ2∈(x,1)f(x)=f(1)+f'(1)(x-1)+\frac{f''(\xi_2)}{2!}(x-1)^2,\ \xi_2\in(x,1)

Noting that f′(0)=f′(1)f'(0)=f'(1), equations (1) and (2) give

f(x)−f(0)(1−x)−f(1)x=f′′(ξ1)2!x(1−x)+f′′(ξ2)2!x(x−1)f(x)-f(0)(1-x)-f(1)x=\frac{f''(\xi_1)}{2!}x(1-x)+\frac{f''(\xi_2)}{2!}x(x-1)

Since ∣f′′(x)∣≤1|f''(x)|\leq1,

∣f(x)−f(0)(1−x)−f(1)x∣≤12x(1−x)+12x(1−x)=x(1−x)2|f(x)-f(0)(1-x)-f(1)x|\leq\frac{1}{2}x(1-x)+\frac{1}{2}x(1-x)=\frac{x(1-x)}{2}

(2) From (1),

−x(1−x)2≤f(x)−f(0)(1−x)−f(1)x≤x(1−x)2-\frac{x(1-x)}{2}\leq f(x)-f(0)(1-x)-f(1)x\leq\frac{x(1-x)}{2}

Integrating both sides of equation (3) over the interval [0,1][0,1] gives

−∫01x(1−x)2dx≤∫01f(x)−f(0)(1−x)−f(1)xdx≤∫01x(1−x)2dx-\int_0^1 \frac{x(1-x)}{2}dx\leq\int_0^1 f(x)-f(0)(1-x)-f(1)x dx\leq\int_0^1 \frac{x(1-x)}{2}dx

that is,

−112≤∫01f(x)dx−f(0)+f(1)2≤112-\frac{1}{12}\leq\int_0^1 f(x)dx-\frac{f(0)+f(1)}{2}\leq\frac{1}{12}

Hence

∣∫01f(x)dx−f(0)+f(1)2∣≤112\left|\int_0^1 f(x)dx-\frac{f(0)+f(1)}{2}\right|\leq\frac{1}{12}

Answer:

(1) When x∈(0,1)x\in(0,1), ∣f(x)−f(0)(1−x)−f(1)x∣≤x(1−x)2|f(x)-f(0)(1-x)-f(1)x|\leq\dfrac{x(1-x)}{2};

(2) ∣∫01f(x)dx−f(0)+f(1)2∣≤112\left|\int_0^1 f(x)dx-\dfrac{f(0)+f(1)}{2}\right|\leq\dfrac{1}{12}.

20. (12 points)

Let the oriented curve LL be the intersection of the sphere x2+y2+z2=2xx^2+y^2+z^2=2x and the plane 2x−z−1=02x-z-1=0, which runs counterclockwise when looked from the positive zz-axis towards the negative zz-axis. Find

∮L(6xyz−yz2)dx+2x2dy+xyzdz.\oint_L (6xyz-yz^2)dx+2x^2dy+xyz dz.
Stokes' formulasurface integralline integral

Answer:

4π255π\frac{4\pi}{25}\sqrt{5}\pi

Approach:

Use Stokes’ formula to turn the line integral into a surface integral.

Steps:

Let the part of the plane 2x−z−1=02x-z-1=0 cut off by the sphere x2+y2+z2=2xx^2+y^2+z^2=2x be the surface Σ\Sigma, with the direction taken to be the upper side; then the unit normal vector of the surface Σ\Sigma is 15(−2,0,1)\frac{1}{\sqrt{5}}(-2,0,1).

By Stokes’ formula:

∮L(6xyz−yz2)dx+2x2dy+xyzdz=15∬Σ∣−201∂∂x∂∂y∂∂z6xyz−yz22x2xyz∣dS\oint_L (6xyz-yz^2)dx+2x^2dy+xyz dz = \frac{1}{\sqrt{5}} \iint_{\Sigma} \left|\begin{matrix}-2 & 0 & 1 \\ \frac{\partial}{\partial x} & \frac{\partial}{\partial y} & \frac{\partial}{\partial z} \\ 6xyz-yz^2 & 2x^2 & xyz\end{matrix}\right| dS=15∬Σ[−2(xz−2x2)+(4xz−6xz+z2)]dS=\frac{1}{\sqrt{5}} \iint_{\Sigma} [-2(xz-2x^2)+(4xz-6xz+z^2)]dS=15∬Σ[−4x(2x−1)+4x2+(2x−1)2]dS=\frac{1}{\sqrt{5}} \iint_{\Sigma} [-4x(2x-1)+4x^2+(2x-1)^2]dS=15∬ΣdS=\frac{1}{\sqrt{5}} \iint_{\Sigma} dS

Since the equation of the projection curve of the surface Σ\Sigma on the xOyxOy plane is 5z−6x+y2=−15z-6x+y^2=-1, the projection region is (x−3/52/5)2+y24/5≤1\left(\frac{x-3/5}{2/5}\right)^2+\frac{y^2}{4/5}\leq1. The area of this projection region is S=π×25×25=4π55S=\pi\times\frac{2}{5}\times\frac{2}{5}=\frac{4\pi}{5\sqrt{5}}, so ∬ΣdS=Scos⁡γ\iint_{\Sigma} dS=\frac{S}{\cos\gamma}, and therefore

∮L(6xyz−yz2)dx+2x2dy+xyzdz=15×4π5/5=4π255π\oint_L (6xyz-yz^2)dx+2x^2dy+xyz dz=\frac{1}{\sqrt{5}}\times\frac{4\pi}{5/\sqrt{5}}=\frac{4\pi}{25}\sqrt{5}\pi

21. (12 points)

Given that the sequences {xn},{yn},{zn}\{x_n\},\{y_n\},\{z_n\} satisfy x0=−1,y0=0,z0=2x_0=-1,y_0=0,z_0=2, and

{xn=−2xn−1+2zn−1yn=−2yn−1−2zn−1zn=−6xn−1−3yn−1+3zn−1\begin{cases} x_n=-2x_{n-1}+2z_{n-1}\\ y_n=-2y_{n-1}-2z_{n-1}\\ z_n=-6x_{n-1}-3y_{n-1}+3z_{n-1} \end{cases}

Denote an=(xnynzn)a_n=\begin{pmatrix}x_n\\y_n\\z_n\end{pmatrix}, and require that an=Aan−1a_n=Aa_{n-1}; write down the matrix AA, and find AnA^n and xn,yn,zn(n=1,2,⋯ )x_n,y_n,z_n(n=1,2,\cdots).

matrix diagonalizationeigenvaluerecurrence sequence

Answer:

A=(−2020−2−2−6−33)A=\begin{pmatrix}-2 & 0 & 2\\0 & -2 & -2\\-6 & -3 & 3\end{pmatrix}

xn=(−1)n⋅2n+8,yn=(−1)n⋅2n−8,zn=12x_n=(-1)^n\cdot2^n+8, y_n=(-1)^n\cdot2^n-8, z_n=12 (n=1,2,⋯ )(n=1,2,\cdots)

Approach:

Solve the recurrence sequence by means of the method of matrix diagonalization.

Steps:

From the given condition,

(xnynzn)=(−2020−2−2−6−33)(xn−1yn−1zn−1)\begin{pmatrix}x_n\\y_n\\z_n\end{pmatrix}=\begin{pmatrix}-2 & 0 & 2\\0 & -2 & -2\\-6 & -3 & 3\end{pmatrix}\begin{pmatrix}x_{n-1}\\y_{n-1}\\z_{n-1}\end{pmatrix}

so A=(−2020−2−2−6−33)A=\begin{pmatrix}-2 & 0 & 2\\0 & -2 & -2\\-6 & -3 & 3\end{pmatrix}.

The characteristic polynomial of the matrix AA is:

f(λ)=∣λE−A∣=∣λ+20−20λ+2263λ−3∣=λ(λ+2)(λ−1)f(\lambda)=|\lambda E-A|=\begin{vmatrix}\lambda+2 & 0 & -2\\0 & \lambda+2 & 2\\6 & 3 & \lambda-3\end{vmatrix}=\lambda(\lambda+2)(\lambda-1)

From f(λ)=0f(\lambda)=0 the eigenvalues of the matrix AA are λ1=0,λ2=−2,λ3=1\lambda_1=0,\lambda_2=-2,\lambda_3=1.

When λ1=0\lambda_1=0, solving the system of equations (0E−A)x=0(0E-A)x=0 gives the fundamental system of solutions p1=(1,−1,1)Tp_1=(1,-1,1)^T;

when λ2=−2\lambda_2=-2, solving the system of equations (−2E−A)x=0(-2E-A)x=0 gives the fundamental system of solutions p2=(−1,2,0)Tp_2=(-1,2,0)^T;

when λ3=1\lambda_3=1, solving the system of equations (E−A)x=0(E-A)x=0 gives the fundamental system of solutions p3=(2,−2,3)Tp_3=(2,-2,3)^T.

Put P=(p1,p2,p3)P=(p_1,p_2,p_3); then P−1AP=Λ=(0000−20001)P^{-1}AP=\Lambda=\begin{pmatrix}0 & 0 & 0\\0 & -2 & 0\\0 & 0 & 1\end{pmatrix}, and moreover P−1=(63−2110−2−11)P^{-1}=\begin{pmatrix}6 & 3 & -2\\1 & 1 & 0\\-2 & -1 & 1\end{pmatrix}.

Hence

An=PΛnP−1=(1−12−12−2103)(0000(−2)n0001)(63−2110−2−11)A^n= P\Lambda^n P^{-1}= \begin{pmatrix}1 & -1 & 2\\-1 & 2 & -2\\1 & 0 & 3\end{pmatrix}\begin{pmatrix}0 & 0 & 0\\0 & (-2)^n & 0\\0 & 0 & 1\end{pmatrix}\begin{pmatrix}6 & 3 & -2\\1 & 1 & 0\\-2 & -1 & 1\end{pmatrix}

Since an=Ana0a_n=A^n a_0, we have

an=Ana0=((−1)n+1⋅2n−4(−1)n+1⋅2n+22(−1)n+1⋅2n+4(−1)n+1⋅2n+22−6−33)(−102)a_n=A^n a_0= \begin{pmatrix}(-1)^{n+1}\cdot2^n-4 & (-1)^{n+1}\cdot2^n+2 & 2\\(-1)^{n+1}\cdot2^n+4 & (-1)^{n+1}\cdot2^n+2 & 2\\-6 & -3 & 3\end{pmatrix}\begin{pmatrix}-1\\0\\2\end{pmatrix}

Hence xn=(−1)n⋅2n+8,yn=(−1)n⋅2n−8,zn=12x_n=(-1)^n\cdot2^n+8, y_n=(-1)^n\cdot2^n-8, z_n=12 (n=1,2,⋯ )(n=1,2,\cdots).

22. (12 points)

Let the population XX follow the uniform distribution on [0,θ][0,\theta], where θ∈(0,+∞)\theta\in(0,+\infty) is an unknown parameter. X1,X2,⋯ ,XnX_1,X_2,\cdots,X_n is a simple random sample from the population XX, and denote

X(n)=max⁡{X1,X2,⋯ ,Xn},Tc=cX(n).X_{(n)}=\max\{X_1,X_2,\cdots,X_n\},\quad T_c=cX_{(n)}.

(1) Find cc such that E(Tc)=θE(T_c)=\theta;

(2) Denote h(c)=E[(Tc−θ)2]h(c)=E\left[(T_c-\theta)^2\right] and find cc such that h(c)h(c) is minimal.

uniform distributionlargest order statisticunbiased estimator

Answer:

(1) c=n+1nc=\frac{n+1}{n}

(2) c=n+2n+1c=\frac{n+2}{n+1}

Approach:

(1) Use the distribution of the largest order statistic to obtain an unbiased estimator.

(2) Find the optimal estimator by minimising the mean square error.

Steps:

(1) The probability density of the random variable XX is f(x)={1θ,0<x<θ0,otherf(x)=\begin{cases}\frac{1}{\theta}, & 0<x<\theta \\ 0, & \text{other}\end{cases}, so the distribution function of the random variable XX is

F(x)={0,x<0xθ,0≤x<θ1,x≥θF(x)=\begin{cases}0, & x<0 \\ \frac{x}{\theta}, & 0\leq x<\theta \\ 1, & x\geq\theta\end{cases}

and then the distribution function of the random variable X(n)X_{(n)} is

FX(n)(x)=P(max⁡{X1,⋯ ,Xn}≤x)=P{X1≤x,⋯ ,Xn≤x}=Fn(x)F_{X_{(n)}}(x)=P(\max\{X_1,\cdots,X_n\}\leq x)=P\{X_1\leq x,\cdots,X_n\leq x\}=F^n(x)

Hence the probability density of X(n)X_{(n)} is fX(n)(x)=nFn−1(x)⋅f(x)=nθnxn−1,0<x<θf_{X_{(n)}}(x)=nF^{n-1}(x)\cdot f(x)=\frac{n}{\theta^n}x^{n-1},0<x<\theta.

Hence E(Tc)=cE(X(n))=c∫0θxnθnxn−1dx=cnn+1θE(T_c)=cE(X_{(n)})=c\int_0^{\theta}x\frac{n}{\theta^n}x^{n-1}dx=c\frac{n}{n+1}\theta; because TcT_c is an unbiased estimator of θ\theta, E(Tc)=θE(T_c)=\theta, and solving gives c=n+1nc=\frac{n+1}{n}.

(2) Since E(Tc2)=c2E(X(n)2)=c2∫0θx2nθnxn−1dx=c2nn+2θ2E(T_c^2)=c^2E(X_{(n)}^2)=c^2\int_0^{\theta}x^2\frac{n}{\theta^n}x^{n-1}dx=c^2\frac{n}{n+2}\theta^2, we have

h(c)=E(Tc−θ)2=E(Tc2)−2θE(Tc)+θ2=c2nn+2θ2−2cnn+1θ2+θ2h(c)=E(T_c-\theta)^2=E(T_c^2)-2\theta E(T_c)+\theta^2=c^2\frac{n}{n+2}\theta^2-2c\frac{n}{n+1}\theta^2+\theta^2

From h′(c)=2cnn+2θ2−2nn+1θ2=0h'(c)=\frac{2cn}{n+2}\theta^2-2\frac{n}{n+1}\theta^2=0 we get c=n+2n+1c=\frac{n+2}{n+1}. Moreover, since h′′(c)=2nn+2θ2>0h''(c)=\frac{2n}{n+2}\theta^2>0, c=n+2n+1c=\frac{n+2}{n+1} is the value at which h(c)h(c) is minimal.

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