Fishing Company A has two types of fishing vessels, the "Standard" vessel and the "Large" vessel. The amount of fish caught by the respective vessels on a typical fishing trip are normally distributed with means and standard deviations as shown in the table.
Mean (kg)Standard deviation (kg)
Standard300σ\sigma
Large540110

  1. (a)

    If a Standard vessel returns with more than 400kg of fish, it is called a Bumper catch. Bumper catches occur 8% of the time. Show that σ≈71.2\sigma \approx 71.2.

  2. (b)

    On a particular fishing trip, Company A sends out 3 Standard vessels and 2 Large vessels, with a target to catch at least 2100kg of fish. Find the probability that the fishing vessels are able to meet their target.

  3. (c)

    State an assumption needed in your calculation in part (b).

  4. (d)

    Fishing Company B operates in the same seas as Fishing Company A. However, Company B has the improved versions of the two types of fishing vessels that Company A has: the "Premium-Standard" vessel and the "Premium-Large" vessel. In a fishing trip, the Premium-Standard vessel is capable of catching 3 times as much fish as the Standard vessel and the Premium-Large vessel is capable of catching 2 times as much fish as Large vessel.

    Company B sends out 1 Premium-Standard vessel and 1 Premium-Large vessel, with the same target to catch at least 2100kg of fish. Find the probability that these two fishing vessels are able to meet their target.

  5. (e)

    It is found that, in a sample of nn randomly chosen fishing trips, the probability that the average catch of a Large vessel being less than 552kg is at least 0.7. Find the least possible value of nn.

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Worked solution

10(a)

1. Set up the probability equation and standardise the variable.

Let SS be the mass of fish caught by a Standard vessel in kg.
S∼N(300,σ2)S \sim \mathrm{N}(300, \sigma^2)
Given P(S>400)=0.08\mathrm{P}(S > 400) = 0.08, we standardise to the standard normal distribution ZZ:
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

2. Use the inverse normal function to solve for the standard deviation.

Using the graphing calculator (inverse normal):
100σ≈1.40507\frac{100}{\sigma} \approx 1.40507
σ=1001.40507\sigma = \frac{100}{1.40507}
σ≈71.171\sigma \approx 71.171
σ≈71.2 (shown)\sigma \approx 71.2 \text{ (shown)}

Answer

σ≈71.2\sigma \approx 71.2

10(b)

1. Define the total catch random variable and calculate its expected value.

Let the total catch be T=S1+S2+S3+L1+L2T = S_1 + S_2 + S_3 + L_1 + L_2.

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

2. Calculate the variance of the total catch.

Var(T)=3Var(S)+2Var(L)\text{Var}(T) = 3\text{Var}(S) + 2\text{Var}(L)

Using the unrounded standard deviation σ≈71.171\sigma \approx 71.171 (derived from part a):
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) \approx 15195.9 + 24200 = 39395.9

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

Since TT is a linear combination of independent normal variables, T∼N(1980,39395.9)T \sim \text{N}(1980, 39395.9).

We require P(T≥2100)\text{P}(T \ge 2100):
P(T≥2100)≈0.27273\text{P}(T \ge 2100) \approx 0.27273
P(T≥2100)≈0.273 (to 3 s.f.)\text{P}(T \ge 2100) \approx 0.273 \text{ (to 3 s.f.)}

Answer

0.2730.273

10(c)

1. Identify the statistical assumption necessary for the linear combination of random variables

In part (b), we calculate the variance of the total catch by summing the variances of the individual catches: Var(S1+S2+S3+L1+L2)=3Var(S)+2Var(L)\mathrm{Var}(S_1 + S_2 + S_3 + L_1 + L_2) = 3\mathrm{Var}(S) + 2\mathrm{Var}(L). This requires the assumption that the random variables are independent.

Answer

The amount of fish caught by each of the vessels are independent of one another.

10(d)

1. Define the distribution for the total catch by Company B's vessels, noting that their catches are multiples of the standard and large vessels.

Let WW be the total catch by 11 Premium-Standard and 11 Premium-Large vessel.
Since the Premium-Standard catches 33 times as much as a Standard vessel, its catch is 3S3S. The Premium-Large catches 22 times as much as a Large vessel, so its catch is 2L2L.
W=3S+2LW = 3S + 2L

E(W)=3E(S)+2E(L)\text{E}(W) = 3\text{E}(S) + 2\text{E}(L)
E(W)=3(300)+2(540)=1980 kg\text{E}(W) = 3(300) + 2(540) = 1980 \text{ kg}

Var(W)=32Var(S)+22Var(L)\text{Var}(W) = 3^2\text{Var}(S) + 2^2\text{Var}(L)
Using σ≈71.171\sigma \approx 71.171 from part (a):
Var(W)=9(71.171)2+4(110)2\text{Var}(W) = 9(71.171)^2 + 4(110)^2
Var(W)≈45587.8+48400=93987.8\text{Var}(W) \approx 45587.8 + 48400 = 93987.8

Thus, W∼N(1980,93987.8)W \sim \text{N}(1980, 93987.8).

2. Calculate the probability that the total catch is at least 2100 kg.

We require P(W≥2100)\text{P}(W \ge 2100).
Using the normal cumulative distribution function on a graphing calculator:
P(W≥2100)≈0.34774\text{P}(W \ge 2100) \approx 0.34774
P(W≥2100)=0.348 (to 3 s.f.)\text{P}(W \ge 2100) = 0.348 \text{ (to 3 s.f.)}

Answer

0.3480.348

10(e)

1. State the distribution of the sample mean.

Let Lˉ\bar{L} be the sample mean catch of a Large vessel for nn trips.
Since the catch of a Large vessel is normally distributed with mean 540540 kg and standard deviation 110110 kg, the sample mean follows:
Lˉ∼N(540,1102n)\bar{L} \sim \mathrm{N}\left(540, \frac{110^2}{n}\right)

2. Set up the probability inequality and standardise.

We are given that P(Lˉ<552)≥0.7\mathrm{P}(\bar{L} < 552) \ge 0.7.
Standardising the variable to the standard normal distribution Z∼N(0,1)Z \sim \mathrm{N}(0, 1):
P(Z<552−540110/n)≥0.7\mathrm{P}\left(Z < \frac{552 - 540}{110/\sqrt{n}}\right) \ge 0.7
P(Z<12n110)≥0.7\mathrm{P}\left(Z < \frac{12\sqrt{n}}{110}\right) \ge 0.7

3. Solve the inequality for $n$ using the inverse normal function.

Using the inverse normal function for an area of 0.70.7, we find the critical zz-value is approximately 0.524400.52440.
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 nn must be an integer (representing the number of trips), the least possible value of nn is 2424.

Answer

2424

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