Respuesta :
Answer:
a. In the explanation.
b. The point estimate of the difference can be calculated as the difference between the sample mean and the population mean:
[tex]d=M-\mu=24.95-23.8=1.15[/tex]
c. Test statistic t = 0.90
P-value = 0.1932
The null hypothesis failed to be rejected.
Step-by-step explanation:
We have a sample, wich mean and standard deviation are calculated as:
[tex]M=\dfrac{1}{14}\sum_{i=1}^{14}(27.8+23.84+25.25+21+17.52+19.61+...+26.94+27.24)\\\\\\ M=\dfrac{349.34}{14}=24.95[/tex]
[tex]s=\sqrt{\dfrac{1}{(n-1)}\sum_{i=1}^{14}(x_i-M)^2}\\\\\\s=\sqrt{\dfrac{1}{13}\cdot [(27.8-(24.95))^2+(23.84-(24.95))^2+...+(27.24-(24.95))^2]}\\\\\\s=\sqrt{\dfrac{1}{13}\cdot [(8.106)+(1.238)+...+(5.23)]}\\\\\\ s=\sqrt{\dfrac{304.036}{13}}=\sqrt{23.39}\\\\\\s=4.8[/tex]
This is a hypothesis test for the population mean.
The claim is that the consumption of milk in the Midwest is significantly higher than the national average.
Then, the null and alternative hypothesis are:
[tex]H_0: \mu=23.8\\\\H_a:\mu> 23.8[/tex]
The significance level is 0.01.
The sample has a size n=14.
The sample mean is M=24.95.
As the standard deviation of the population is not known, we estimate it with the sample standard deviation, that has a value of s=4.8.
The estimated standard error of the mean is computed using the formula:
[tex]s_M=\dfrac{s}{\sqrt{n}}=\dfrac{4.8}{\sqrt{14}}=1.28[/tex]
Then, we can calculate the t-statistic as:
[tex]t=\dfrac{M-\mu}{s/\sqrt{n}}=\dfrac{24.95-23.8}{1.28}=\dfrac{1.15}{1.28}=0.9[/tex]
The degrees of freedom for this sample size are:
[tex]df=n-1=14-1=13[/tex]
This test is a right-tailed test, with 13 degrees of freedom and t=0.9, so the P-value for this test is calculated as (using a t-table):
[tex]\text{P-value}=P(t>0.9)=0.1932[/tex]
As the P-value (0.1932) is bigger than the significance level (0.01), the effect is not significant.
The null hypothesis failed to be rejected.
There is not enough evidence to support the claim that the consumption of milk in the Midwest is significantly higher than the national average.