Answer:
[tex]t=\frac{26.8-29.9}{\frac{2.7}{\sqrt{9}}}=-3.44[/tex]
[tex]df=n-1=9-1=8[/tex]
[tex]p_v =P(t_{(8)}<-3.44)=0.0044[/tex]
Since the p value is lower than the significance level we have enough evidence to reject the null hypothesis and is not enough evidence to conclude that the claim is true.
Step-by-step explanation:
Data given
[tex]\bar X=26.8[/tex] represent the sample mean
[tex]s=2.7[/tex] represent the sample standard deviation
[tex]n=9[/tex] sample size
[tex]\mu_o =29.9[/tex] represent the value that we want to test
[tex]\alpha=0.05[/tex] represent the significance level for the hypothesis test.
t would represent the statistic (variable of interest)
[tex]p_v[/tex] represent the p value for the test (variable of interest)
System of hypothesis
We need to conduct a hypothesis in order to check if the true mean exceed 29.9 or no, the system of hypothesis would be:
Null hypothesis:[tex]\mu \geq 29.9[/tex]
Alternative hypothesis:[tex]\mu < 29.9[/tex]
The statistic is given by:
[tex]t=\frac{\bar X-\mu_o}{\frac{s}{\sqrt{n}}}[/tex] (1)
Calculate the statistic
We can replace in formula (1) the info given like this:
[tex]t=\frac{26.8-29.9}{\frac{2.7}{\sqrt{9}}}=-3.44[/tex]
P-value
The degrees of freedom are given by:
[tex]df=n-1=9-1=8[/tex]
Since is a one sided test the p value would be:
[tex]p_v =P(t_{(8)}<-3.44)=0.0044[/tex]
Conclusion
Since the p value is lower than the significance level we have enough evidence to reject the null hypothesis and is not enough evidence to conclude that the claim is true.