在本题中,你应该清晰地写出你使用的所有分布,以及相应参数的值。 当地的一家超市销售两种土豆:褐土豆(Russet potatoes)和荷兰土豆(Holland potatoes)。褐土豆的质量(以克为单位)服从分布 N(200,302)\mathrm{N}(200, 30^2),荷兰土豆的质量(以克为单位)服从分布 N(150,242)\mathrm{N}(150, 24^2)。

  1. (i)

    求随机挑选的 3 个荷兰土豆的总质量小于随机挑选的 1 个褐土豆质量的两倍的概率。

  2. (ii)

    超市决定将土豆包装成混合包。每个混合包包含随机挑选的 5 个褐土豆 and 4 个荷兰土豆。已知一个随机挑选的混合包的质量与 1600 克之差在 kk 克以内的概率为 0.775。求 kk。

  3. (iii)

    随机选择 40 个混合包捐赠给有需要的家庭。使用在 (ii) 中求得的 kk 值,求至多有 5 个混合包的质量与 1600 克之差不在 kk 克以内的概率。

  4. (iv)

    简述在第 (i)、(ii) 和 (iii) 部分的计算中所需要的一个假设。

  5. (v)

    该超市最近引入了一种新土豆,称为新土豆。新土豆的平均质量为 55 克,标准差为 13 克。

    求随机抽取的 100 个新土豆的平均质量不超过 58 克的概率的近似值。

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完整解法

12(i)

1. Define the random variable for the linear combination and calculate its expected value.

Let HH and RR be the masses of a randomly chosen Holland and Russet potato respectively.
Let W=H1+H2+H3−2RW = H_1 + H_2 + H_3 - 2R, where H1,H2,H3H_1, H_2, H_3 are independent observations of HH.
E(W)=3E(H)−2E(R)\mathrm{E}(W) = 3\mathrm{E}(H) - 2\mathrm{E}(R)
=3(150)−2(200)=50= 3(150) - 2(200) = 50

2. Calculate the variance of the linear combination and state its overall normal distribution as required by the question context.

Var(W)=3Var(H)+(−2)2Var(R)\mathrm{Var}(W) = 3\mathrm{Var}(H) + (-2)^2\mathrm{Var}(R)
=3(242)+4(302)= 3(24^2) + 4(30^2)
=1728+3600=5328= 1728 + 3600 = 5328
Since any linear combination of independent normal variables is also normally distributed, we state the distribution as:
W∼N(50,5328)W \sim \mathrm{N}(50, 5328)

3. Find the probability that the combination is less than zero.

We require P(H1+H2+H3<2R)\mathrm{P}(H_1 + H_2 + H_3 < 2R), which is equivalent to P(W<0)\mathrm{P}(W < 0).
Using a graphing calculator:
P(W<0)≈0.24667\mathrm{P}(W < 0) \approx 0.24667
≈0.247 (to 3 s.f.)\approx 0.247 \text{ (to 3 s.f.)}

答案

0.2470.247

12(ii)

1. Define the random variable for the variety pack and calculate its expected value and variance.

Let VV be the total mass of the variety pack.
V=R1+R2+R3+R4+R5+H1+H2+H3+H4V = R_1 + R_2 + R_3 + R_4 + R_5 + H_1 + H_2 + H_3 + H_4
E(V)=5(200)+4(150)=1600\text{E}(V) = 5(200) + 4(150) = 1600
Var(V)=5(302)+4(242)=6804\text{Var}(V) = 5(30^2) + 4(24^2) = 6804
V∼N(1600,6804)V \sim \text{N}(1600, 6804)

2. Set up the probability equation based on the given information.

P(1600−k<V<1600+k)=0.775\text{P}(1600 - k < V < 1600 + k) = 0.775

3. Solve for $k$ using the symmetry of the normal distribution and the inverse normal function.

By the symmetry of the normal distribution:
P(V<1600+k)=0.5+0.7752=0.8875\text{P}(V < 1600 + k) = 0.5 + \frac{0.775}{2} = 0.8875
Using the inverse normal function on a graphing calculator:
1600+k≈1700.0821600 + k \approx 1700.082
k≈100.082k \approx 100.082
k=100 (to 3 s.f.)k = 100 \text{ (to 3 s.f.)}

答案

100100 (to 3 s.f.)

12(iii)

1. Identify the binomial model and the probability of a pack not being within $k$ grams.

Let YY be the number of variety packs out of 4040 that are not within kk grams of 16001600 grams.
From part (ii), the probability that a pack is within kk grams is 0.7750.775.
Thus, the probability that a pack is not within kk grams is 1−0.775=0.2251 - 0.775 = 0.225.
Y∼B(40,0.225)Y \sim \mathrm{B}(40, 0.225)

2. Calculate the probability that at most 5 packs are not within $k$ grams.

We require P(Y≤5)\mathrm{P}(Y \le 5).
Using a graphing calculator to compute the cumulative binomial probability:
P(Y≤5)=0.086522…\mathrm{P}(Y \le 5) = 0.086522\dots
P(Y≤5)≈0.0865 (to 3 s.f.)\mathrm{P}(Y \le 5) \approx 0.0865 \text{ (to 3 s.f.)}

答案

0.08650.0865

12(iv)

1. State the necessary assumption for combining random variables and using the binomial distribution

The calculations for the sum and difference of normal variables in parts (i) and (ii), as well as the binomial trials of variety packs in part (iii), all mathematically require the individual random events to be independent.

答案

The masses of all the potatoes chosen are independent of one another.

12(v)

1. Define the sample mean random variable and state its approximate distribution using the Central Limit Theorem.

Let Wˉ\bar{W} be the sample mean mass of 100100 New potatoes.
Since the sample size n=100n = 100 is large (n≥30n \ge 30), by the Central Limit Theorem, Wˉ\bar{W} is approximately normally distributed.
Wˉ∼N(55,132100) approximately\bar{W} \sim \mathrm{N}\left(55, \frac{13^2}{100}\right) \text{ approximately}
Wˉ∼N(55,1.69)\bar{W} \sim \mathrm{N}(55, 1.69)

2. Calculate the probability that the sample mean is not more than 58 grams.

We need to find P(Wˉ≤58)\mathrm{P}(\bar{W} \le 58).
Using a graphing calculator,
P(Wˉ≤58)≈0.989495\mathrm{P}(\bar{W} \le 58) \approx 0.989495
P(Wˉ≤58)=0.989 (to 3 s.f.)\mathrm{P}(\bar{W} \le 58) = 0.989 \text{ (to 3 s.f.)}

答案

0.989

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