The time taken, TT (in minutes), for a 17-year-old student to complete a 5-km run is a random variable with mean 30. After a new training programme is introduced for these students, a random sample of nn students is taken. The mean time and standard deviation for the sample are found to be 28.9 minutes and 4.0 minutes respectively.

  1. ((a))

    Find the unbiased estimate of the population variance in terms of nn.

  2. ((b))

    Using n=40n = 40,

    1. ((i))

      carry out a test at the 10% significance level to determine if the mean time taken has changed. State appropriate hypotheses for the test and define any symbols you use.

    2. ((ii))

      State what it means by the p-value in this context.

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Worked solution

9((a))

1. Calculate the sample variance from the given sample standard deviation

Sample variance=4.02=16\text{Sample variance} = 4.0^2 = 16

2. Calculate the unbiased estimate of the population variance

s2=nn−1×Sample variance=nn−1(16)=16nn−1s^2 = \frac{n}{n-1} \times \text{Sample variance} = \frac{n}{n-1}(16) = \frac{16n}{n-1}

Answer

16nn−1\frac{16n}{n-1}

9((b))((i))

1. State the hypotheses and define the population mean symbol.

Let μ\mu be the population mean time taken (in minutes) by a 17-year-old student to complete a 5-km run after the new training programme.
H0:μ=30H_0: \mu = 30
H1:μ≠30H_1: \mu \neq 30

2. Calculate the unbiased estimate of the population variance and state the test statistic.

From part (a), the unbiased estimate of the population variance is s2=nn−1σn2s^2 = \frac{n}{n-1} \sigma_n^2.
For n=40n=40 and sample standard deviation σn=4.0\sigma_n = 4.0:
s2=4039(4.0)2=64039≈16.410s^2 = \frac{40}{39}(4.0)^2 = \frac{640}{39} \approx 16.410
Under H0H_0, since n=40n=40 is large (n≥30n \ge 30), the sample mean Xˉ\bar{X} is approximately normally distributed by the Central Limit Theorem.
The test statistic is Z=Xˉ−μ0S/n∼N(0,1)Z = \frac{\bar{X} - \mu_0}{S/\sqrt{n}} \sim N(0, 1) approximately.
z=28.9−30640/3940=−1.11639≈−1.71737z = \frac{28.9 - 30}{\sqrt{\frac{640/39}{40}}} = \frac{-1.1}{\sqrt{\frac{16}{39}}} \approx -1.71737

3. Calculate the p-value for the two-tailed test.

p-value=2×P(Z≤−1.71737)p\text{-value} = 2 \times P(Z \le -1.71737)
p-value≈0.085906≈0.0859 (to 3 s.f.)p\text{-value} \approx 0.085906 \approx 0.0859 \text{ (to 3 s.f.)}

4. Compare the p-value with the significance level and state the conclusion.

Since the pp-value =0.0859<0.10= 0.0859 < 0.10, we reject H0H_0.
There is sufficient evidence at the 10% level of significance to conclude that the mean time taken has changed.

Answer

H0:μ=30H_0: \mu = 30
H1:μ≠30H_1: \mu \neq 30
p-value=0.0859p\text{-value} = 0.0859
Reject H0H_0; there is sufficient evidence at the 10% significance level to conclude that the mean time taken has changed.

9((b))((ii))

1. State the contextual meaning of the $p$-value.

The pp-value is the probability of obtaining a sample mean time of 28.9 minutes or a value more extreme, assuming that the true population mean time taken by the students is 30 minutes.

Answer

The pp-value is the probability of obtaining a sample mean time of 28.9 minutes or a value more extreme, assuming that the true population mean time taken by the students is 30 minutes.

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