The owner of Eng Choo Farm claims that the eggs produced at his farm has an average cholesterol content of μ0\mu_0 mg per egg. The Health Promotion Agency took a random sample of 16 eggs from the farm and measured the cholesterol content, xx mg, of each egg. The results are summarized as follows: ∑x=2848\sum x = 2848 and ∑x2=509884\sum x^2 = 509884.

  1. (a)

    Find the set of values of μ0\mu_0 for which the owner's claim will not be rejected at the 5% significance level.

  2. (b)

    A second random sample of 36 eggs from the farm is taken and the cholesterol content of each egg is measured. The sample mean and the sample variance are found to be 185 mg and 120 mg2^2 respectively.

    Combining the two samples into a single sample, find unbiased estimates of the population mean μ\mu mg and population variance σ2\sigma^2 mg2^2 of the cholesterol content of the eggs produced at the farm.

    Using this combined sample, the null hypothesis μ=180\mu = 180 is tested against the alternative hypothesis μ>180\mu > 180 at 5% significance level. Find the pp-value of the test and explain the meaning of this pp-value in the context of the question.

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Worked solution

9(a)

1. Find the sample mean and unbiased estimate of variance

xˉ=∑xn=284816=178\bar{x} = \frac{\sum x}{n} = \frac{2848}{16} = 178
s2=1n−1(∑x2−(∑x)2n)=115(509884−2848216)=294015=196s^2 = \frac{1}{n-1}\left(\sum x^2 - \frac{(\sum x)^2}{n}\right) = \frac{1}{15}\left(509884 - \frac{2848^2}{16}\right) = \frac{2940}{15} = 196
So the estimated standard deviation is s=14s = 14 and sn=1416=3.5\dfrac{s}{\sqrt{n}} = \dfrac{14}{\sqrt{16}} = 3.5.

2. Set up the two-tail acceptance condition

The owner claims the mean is μ0\mu_0, so we test H0:μ=μ0H_0: \mu = \mu_0 against H1:μ≠μ0H_1: \mu \neq \mu_0 (a 2-tail test) at the 5% level. Assuming the population is normal and using Z=xˉ−μ0s/nZ = \dfrac{\bar{x} - \mu_0}{s/\sqrt{n}}, the claim is not rejected when
−1.95996<178−μ03.5<1.95996.-1.95996 < \frac{178 - \mu_0}{3.5} < 1.95996.

3. Solve the inequality for μ₀

∣178−μ0∣<1.95996×3.5=6.8599|178 - \mu_0| < 1.95996 \times 3.5 = 6.8599
178−6.8599<μ0<178+6.8599178 - 6.8599 < \mu_0 < 178 + 6.8599
171.14<μ0<184.86171.14 < \mu_0 < 184.86
Hence the set of values is {μ0:171<μ0<185}\{\mu_0 : 171 < \mu_0 < 185\}.

Answer

{μ0∈R:171<μ0<185}\{\mu_0 \in \mathbb{R} : 171 < \mu_0 < 185\} (more precisely 171.14<μ0<184.86171.14 < \mu_0 < 184.86).

9(b)

1. Find the sum and sum of squares of $x$ for the second sample.

For the second sample, n2=36n_2 = 36 and xˉ2=185\bar{x}_2 = 185.
∑x2=36×185=6660\sum x_2 = 36 \times 185 = 6660

Using the biased sample variance formula 1n2(∑x22−(∑x2)2n2)=120\frac{1}{n_2}\left(\sum x_2^2 - \frac{(\sum x_2)^2}{n_2}\right) = 120:
136(∑x22−6660236)=120\frac{1}{36}\left(\sum x_2^2 - \frac{6660^2}{36}\right) = 120
∑x22=36(120)+36(1852)=4320+1232100=1236420\sum x_2^2 = 36(120) + 36(185^2) = 4320 + 1232100 = 1236420

2. Calculate the combined unbiased estimates for the population mean and variance.

For the combined sample, n=16+36=52n = 16 + 36 = 52.
∑x=2848+6660=9508\sum x = 2848 + 6660 = 9508
∑x2=509884+1236420=1746304\sum x^2 = 509884 + 1236420 = 1746304

Unbiased estimate of population mean, μ^\hat{\mu}:
xˉ=950852=237713≈182.85 mg\bar{x} = \frac{9508}{52} = \frac{2377}{13} \approx 182.85 \text{ mg}

Unbiased estimate of population variance, s2s^2:
s2=1n−1(∑x2−(∑x)2n)s^2 = \frac{1}{n-1} \left( \sum x^2 - \frac{(\sum x)^2}{n} \right)
s2=151(1746304−9508252)=151(1746304−9040206452)s^2 = \frac{1}{51} \left( 1746304 - \frac{9508^2}{52} \right) = \frac{1}{51} \left( 1746304 - \frac{90402064}{52} \right)
s2=33812221≈153.00 mg2s^2 = \frac{33812}{221} \approx 153.00 \text{ mg}^2

3. State the hypotheses and find the $p$-value using a test statistic.

H0:μ=180H_0: \mu = 180
H1:μ>180H_1: \mu > 180

Under H0H_0, since the sample size n=52n = 52 is large, by the Central Limit Theorem the sample mean is approximately normally distributed. The test statistic is:
Z=Xˉ−180s/52∼N(0,1) approximately.Z = \frac{\bar{X} - 180}{s / \sqrt{52}} \sim N(0, 1) \text{ approximately.}

Using a graphing calculator (Z-Test) with μ0=180\mu_0 = 180, xˉ=237713\bar{x} = \frac{2377}{13}, sx=33812221s_x = \sqrt{\frac{33812}{221}}, and n=52n = 52:
z≈1.659z \approx 1.659
p-value≈0.0485p\text{-value} \approx 0.0485 (to 3 s.f.)

4. Explain the meaning of the $p$-value in the context of the question.

The pp-value of 0.04850.0485 is the probability of obtaining a sample mean cholesterol content of 237713\frac{2377}{13} mg (approx. 182.8182.8 mg) or more, assuming that the true population mean cholesterol content of the eggs is 180180 mg.

Answer

Unbiased estimate of population mean =237713≈183= \frac{2377}{13} \approx 183 mg; Unbiased estimate of population variance =33812221≈153= \frac{33812}{221} \approx 153 mg2^2; pp-value ≈0.0485\approx 0.0485. The pp-value is the probability of obtaining a sample mean cholesterol content of 237713\frac{2377}{13} mg or more, assuming that the true population mean cholesterol content is 180180 mg.

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