渔业公司 A 拥有两种类型的渔船:“标准”型渔船和“大型”型渔船。在一次常规的捕鱼行程中,各自定义渔船所捕获的鱼量均服从正态分布,其均值和标准差如表所示。

  1. (a)

    如果一艘“标准”型渔船返回时捕获的鱼量超过 400kg,则被称为“丰收”。丰收的发生概率为 8%。证明 σ≈71.2\sigma \approx 71.2。

  2. (b)

    在一次特定的捕鱼出海中,A 公司派出了 3 艘标准船和 2 艘大型船,目标是捕获至少 2100kg 的鱼。求这些渔船能够达到目标的概率。

  3. (c)

    指出你在第 (b) 问计算中所需的一个假设。

  4. (d)

    渔业公司 B 在与渔业公司 A 相同的海域运营。然而,公司 B 拥有公司 A 那两种渔船的改进版本:“高级标准型”渔船和“高级大型”渔船。在一次出海捕鱼中,高级标准型渔船的捕鱼量是标准型渔船的 3 倍,而高级大型渔船的捕鱼量是大型渔船的 2 倍。

    公司 B 派出 1 艘高级标准型渔船和 1 艘高级大型渔船,其目标同样是捕获至少 2100kg 的鱼。求这两艘渔船能够达到目标的概率。

  5. (e)

    已知在随机抽取的 nn 次出海捕鱼样本中,大型渔船的平均捕鱼量少于 552kg 的概率至少为 0.7。求 nn 的最小可能值。

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完整解法

10(a)

1. Formulate the probability equation for the Standard vessel's catch.

Let SS be the mass of fish caught by a Standard vessel.
S∼N(300,σ2)S \sim \mathrm{N}(300, \sigma^2)
It is given that P(S>400)=0.08\mathrm{P}(S > 400) = 0.08.

2. Standardise the variable and use the inverse normal function.

P(Z>400−300σ)=0.08\mathrm{P}\left(Z > \frac{400 - 300}{\sigma}\right) = 0.08
P(Z<100σ)=1−0.08=0.92\mathrm{P}\left(Z < \frac{100}{\sigma}\right) = 1 - 0.08 = 0.92
Using the graphing calculator to find the inverse normal of 0.920.92:
100σ≈1.40507\frac{100}{\sigma} \approx 1.40507

3. Solve for the standard deviation $\sigma$.

σ≈1001.40507\sigma \approx \frac{100}{1.40507}
σ≈71.171\sigma \approx 71.171
σ≈71.2 (shown)\sigma \approx 71.2 \text{ (shown)}

答案

σ≈71.2\sigma \approx 71.2 (shown)

10(b)

1. Define the random variable for the total catch and calculate its mean and variance.

Let T=S1+S2+S3+L1+L2T = S_1 + S_2 + S_3 + L_1 + L_2 be the total amount of fish caught by the 5 vessels.
Using σ=71.171\sigma = 71.171 from part (a):
E(T)=3E(S)+2E(L)\text{E}(T) = 3\text{E}(S) + 2\text{E}(L)
E(T)=3(300)+2(540)=1980\text{E}(T) = 3(300) + 2(540) = 1980

Var(T)=3Var(S)+2Var(L)\text{Var}(T) = 3\text{Var}(S) + 2\text{Var}(L)
Var(T)=3(71.171)2+2(110)2\text{Var}(T) = 3(71.171)^2 + 2(110)^2
Var(T)=15195.9+24200=39395.9\text{Var}(T) = 15195.9 + 24200 = 39395.9

Thus, T∼N(1980,39395.9)T \sim \text{N}(1980, 39395.9).

2. Calculate the probability that the total catch meets the target.

We need to find the probability that the total catch is at least 2100 kg, which is P(T≥2100)\text{P}(T \ge 2100).

Using a graphing calculator:
P(T≥2100)=0.27272…\text{P}(T \ge 2100) = 0.27272\dots
P(T≥2100)≈0.273 (to 3 s.f.)\text{P}(T \ge 2100) \approx 0.273 \text{ (to 3 s.f.)}

答案

0.2730.273

10(c)

1. State the statistical assumption required to sum the variances of the individual random variables.

In part (b), the variance of the total catch is calculated by summing the variances of the individual catches. This requires the assumption that the amount of fish caught by each vessel is independent of the amount caught by the other vessels.

答案

The amount of fish caught by each vessel is independent of the amount caught by the other vessels.

10(d)

1. Define the random variable for the total catch of Company B and calculate its expectation.

Let TBT_B be the total catch for Company B.
Since the vessels catch scalar multiples of the original amounts, TB=3S+2LT_B = 3S + 2L.
E(TB)=3E(S)+2E(L)\text{E}(T_B) = 3\text{E}(S) + 2\text{E}(L)
E(TB)=3(300)+2(540)=1980\text{E}(T_B) = 3(300) + 2(540) = 1980

2. Calculate the variance of the total catch, taking care to square the scaling constants.

Using the more precise value σ≈71.171\sigma \approx 71.171 from part (a):
Var(TB)=32Var(S)+22Var(L)\text{Var}(T_B) = 3^2\text{Var}(S) + 2^2\text{Var}(L)
Var(TB)=9(71.171)2+4(1102)\text{Var}(T_B) = 9(71.171)^2 + 4(110^2)
Var(TB)≈45587.5+48400=93987.5\text{Var}(T_B) \approx 45587.5 + 48400 = 93987.5

3. Find the probability that the target of at least 2100kg is met.

TB∼N(1980,93987.5)T_B \sim \text{N}(1980, 93987.5)
P(TB≥2100)≈0.34773≈0.348 (to 3 s.f.)\text{P}(T_B \ge 2100) \approx 0.34773 \approx 0.348 \text{ (to 3 s.f.)}

答案

0.348

10(e)

1. State the distribution of the sample mean.

Let LL be the amount of fish caught by a Large vessel. From the given information, L∼N(540,1102)L \sim \text{N}(540, 110^2).
For a sample of nn trips, the sample mean Lˉ\bar{L} follows a normal distribution:
Lˉ∼N(540,1102n)\bar{L} \sim \text{N}\left(540, \frac{110^2}{n}\right)

2. Set up an inequality by standardising the normal variable.

We are given that P(Lˉ<552)≥0.7\text{P}(\bar{L} < 552) \ge 0.7.
Standardising the variable gives:
P(Z<552−540110/n)≥0.7\text{P}\left(Z < \frac{552 - 540}{110/\sqrt{n}}\right) \ge 0.7
P(Z<12n110)≥0.7\text{P}\left(Z < \frac{12\sqrt{n}}{110}\right) \ge 0.7

3. Solve the inequality to find the least possible integer value for $n$.

Using the inverse normal distribution, for P(Z<z)=0.7\text{P}(Z < z) = 0.7, the critical zz-value is z≈0.52440z \approx 0.52440.
12n110≥0.52440\frac{12\sqrt{n}}{110} \ge 0.52440
n≥110×0.5244012\sqrt{n} \ge \frac{110 \times 0.52440}{12}
n≥4.8070\sqrt{n} \ge 4.8070
n≥23.107n \ge 23.107
Since the sample size nn must be an integer, the least possible value of nn is 2424.

答案

2424

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