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S3 2026 Jan A Q7

A Level / Edexcel / S3

IAL 2026 Jan A Paper · Question 7

题目

Problem

7.

(i) As part of a recruitment exercise candidates are required to complete three separate tasks. The times taken, AA, BB and CC, in minutes, for candidates to complete the three tasks are such that

A∼N(21,22)A \sim N(21, 2^2), B∼N(32,72)B \sim N(32, 7^2) and C∼N(45,92)C \sim N(45, 9^2)

The time taken by an individual candidate to complete each task is assumed to be independent of the time taken to complete each of the other tasks.

A candidate is selected at random.

(a) Find the probability that the candidate takes a total time of more than 90 minutes to complete all three tasks.

(4)

(b) Find P(A>B)P(A > B)

(4)

(ii) A simple random sample, X1,X2,X3,X4X_1, X_2, X_3, X_4, is taken from a normal population with mean μ\mu and standard deviation σ\sigma

Given that

X‾=X1+X2+X3+X44\overline{X} = \frac{X_1 + X_2 + X_3 + X_4}{4}

and that

P(X1>X‾+kσ)=0.1P(X_1 > \overline{X} + k\sigma) = 0.1

where kk is a constant,

find the value of kk, giving your answer correct to 3 significant figures. You should show all stages of your working.

(7)
(Total for Question 7 is 15 marks)
(Total for Paper is 75 marks)
题目中文翻译

(i) 作为招聘活动的一部分,候选人需要完成三个独立任务。完成三个任务所用的时间分别为 AA、BB 和 CC(单位:分钟),且

A∼N(21,22)A\sim N(21,2^2)、B∼N(32,72)B\sim N(32,7^2)、C∼N(45,92)C\sim N(45,9^2)

假设候选人完成每个任务所需时间彼此独立。

随机选取一名候选人。

(a) 求该候选人完成全部三个任务所用总时间超过 90 分钟的概率。

(4)

(b) 求 P(A>B)P(A>B)。

(4)

(ii) 从一个均值为 μ\mu、标准差为 σ\sigma 的正态总体中抽取一个简单随机样本 X1,X2,X3,X4X_1,X_2,X_3,X_4。

已知

X‾=X1+X2+X3+X44.\overline{X}=\frac{X_1+X_2+X_3+X_4}{4}.

并且

P(X1>X‾+kσ)=0.1.P(X_1>\overline{X}+k\sigma)=0.1.

其中 kk 为常数。

求 kk 的值,答案保留 3 位有效数字。你应写出全部过程。

(7)

解答

(i)(a)

解法一

思路

展开

令总时间 T=A+B+CT=A+B+C。独立正态变量之和仍服从正态分布,其均值相加、方差相加。求出 TT 的分布后,将 90 标准化并计算上尾概率。

答题过程

展开

Let

T=A+B+C.T=A+B+C.

Since AA, BB and CC are independent normal random variables,

E(T)= 21+32+45= 98,\begin{align*} E(T) =&\,21+32+45\\ =&\,98, \end{align*}

and

Var⁡(T)= 22+72+92= 134.\begin{align*} \operatorname{Var}(T) =&\,2^2+7^2+9^2\\ =&\,134. \end{align*}

Therefore,

T∼N⁡(98,134).T\sim\operatorname{N}(98,134).

Hence,

P(T>90)= P(Z>90−98134)= P(Z>−0.69109…)= 0.755(3 s.f.).\begin{align*} P(T>90) =&\,P\big(Z>\frac{90-98}{\sqrt{134}}\big)\\ =&\,P(Z>-0.69109\ldots)\\ =&\,\boxed{0.755}\quad\text{(3 s.f.)}. \end{align*}

(i)(b)

解法一

思路

展开

把事件 A>BA>B 改写为 A−B>0A-B>0。由于 AA、BB 独立,差 A−BA-B 仍为正态变量;其均值相减,但方差仍相加。确定差的分布后计算超过 0 的概率。

答题过程

展开

Let

D=A−B.D=A-B.

Since AA and BB are independent,

E(D)= 21−32= −11,\begin{align*} E(D) =&\,21-32\\ =&\,-11, \end{align*}

and

Var⁡(D)= 22+72= 53.\begin{align*} \operatorname{Var}(D) =&\,2^2+7^2\\ =&\,53. \end{align*}

Thus,

D∼N⁡(−11,53).D\sim\operatorname{N}(-11,53).

Therefore,

P(A>B)= P(D>0)= P(Z>0−(−11)53)= P(Z>1.51097…)= 0.0654(3 s.f.).\begin{align*} P(A>B) =&\,P(D>0)\\ =&\,P\big(Z>\frac{0-(-11)}{\sqrt{53}}\big)\\ =&\,P(Z>1.51097\ldots)\\ =&\,\boxed{0.0654}\quad\text{(3 s.f.)}. \end{align*}

(ii)

解法一

思路

展开

先把原事件改写为 X1−X‾>kσX_1-\overline X>k\sigma。由于 X‾\overline X 中含有 X1X_1,不能错误地把 X1X_1 与 X‾\overline X 当成独立变量;应先将差展开成 X1,X2,X3,X4X_1,X_2,X_3,X_4 的线性组合,再利用样本各项独立来求其均值和方差。最后用上尾概率 0.10.1 对应的标准正态分位数 1.28161.2816 求 kk。

答题过程

展开

Define

D=X1−X‾.D=X_1-\overline{X}.

Then

D= X1−X1+X2+X3+X44= 3X1−X2−X3−X44.\begin{align*} D =&\,X_1-\frac{X_1+X_2+X_3+X_4}{4}\\ =&\,\frac{3X_1-X_2-X_3-X_4}{4}. \end{align*}

Since X1,X2,X3,X4X_1,X_2,X_3,X_4 are independent and each has mean μ\mu and variance σ2\sigma^2,

E(D)= 3μ−μ−μ−μ4= 0,\begin{align*} E(D) =&\,\frac{3\mu-\mu-\mu-\mu}{4}\\ =&\,0, \end{align*}

and

Var⁡(D)= 9σ2+σ2+σ2+σ242= 12σ216= 0.75σ2.\begin{align*} \operatorname{Var}(D) =&\,\frac{9\sigma^2+\sigma^2+\sigma^2+\sigma^2}{4^2}\\ =&\,\frac{12\sigma^2}{16}\\ =&\,0.75\sigma^2. \end{align*}

As DD is a linear combination of independent normal random variables,

D∼N⁡(0,0.75σ2).D\sim\operatorname{N}(0,0.75\sigma^2).

The given probability becomes

P(D>kσ)=0.1.P(D>k\sigma)=0.1.

Since the standard deviation of DD is 0.75 σ\sqrt{0.75}\,\sigma,

P(Z>k0.75)=0.1.P\big(Z>\frac{k}{\sqrt{0.75}}\big)=0.1.

The standard normal value with upper-tail probability 0.10.1 is 1.28161.2816. Therefore,

k0.75= 1.2816k= 0.75(1.2816)= 1.10990…= 1.11(3 s.f.).\begin{align*} \frac{k}{\sqrt{0.75}} =&\,1.2816\\ k =&\,\sqrt{0.75}(1.2816)\\ =&\,1.10990\ldots\\ =&\,\boxed{1.11}\quad\text{(3 s.f.)}. \end{align*}