Answer:
![z = (\bar X -\mu)/(\sigma_(\bar X))= (70.9-71.5)/(0.77)=-0.779](https://img.qammunity.org/2021/formulas/mathematics/college/qi08sbid7sqm6d34o6whi9brczplzy371l.png)
From this result we can conclude that the value of 70.9 is 0.78 deviation below the true mean of 71.5 and that can be considered as unusual. If we conduct a hypothesis test or a confidence interval we will see that we have enough evidence to conclude that the true mean is not significantly different from 71.5.
Explanation:
For this case from all the population we know that the population mean and deviation are:
![\mu = 71.5,\sigma = 4.87](https://img.qammunity.org/2021/formulas/mathematics/college/ajbi2kcicl1fvb20a4fct1pr4bhsfaqd48.png)
And we take a random sample of size n =40 and we got a sample mean calculated with the following formula:
![\bar X =(\sum_(i=1)^n X_i)/(n)= (\sum_(i=1)^(40) X_i)/(40)=70.9](https://img.qammunity.org/2021/formulas/mathematics/college/isx5m9m7ipgqlha6k53wjv9cusn69w4fjf.png)
And we want to test if this value is unusually low.
Since the sample size is large n>30 we can use the central limit theorem who says that the distribution for the sample mean is given by:
![\bar X \sim N (\mu , (\sigma)/(√(n)))](https://img.qammunity.org/2021/formulas/mathematics/college/h3wmwki3tq42mmxu64utlbhg8g7ywhn5z5.png)
And on this case if we replace the values that we have we got:
![\bar X \sim N (\mu_(\bar X)=71.5,\sigma_(\bar X)= (\sigma)/(√(n))=(4.87)/(√(40))=0.77)](https://img.qammunity.org/2021/formulas/mathematics/college/vkahh7gxnp8lk32yiachg71alw9n9ynv32.png)
For this case we can calculate how many deviations above or below is our calculated value from the sample of size 40, using the z score given by:
![z = (\bar X -\mu)/(\sigma_(\bar X))= (70.9-71.5)/(0.77)=-0.779](https://img.qammunity.org/2021/formulas/mathematics/college/qi08sbid7sqm6d34o6whi9brczplzy371l.png)
From this result we can conclude that the value of 70.9 is 0.78 deviation below the true mean of 71.5 and that can be considered as unusual. If we conduct a hypothesis test or a confidence interval we will see that we have enough evidence to conclude that the true mean is not significantly different from 71.5.