Answer:
Null hypothesis:[tex]\mu = 52.6[/tex]
Alternative hypothesis:[tex]\mu \neq 52.6[/tex]
[tex]z=\frac{52.8-52.6}{\frac{1.6}{\sqrt{250}}}=1.976[/tex]
[tex]p_v =2*P(z>1.976)=0.0482[/tex]
Since the p value is lower than the significance level wedon't have enough evidence to conclude that the true mean is significantly different from 52.6 MPG.
Step-by-step explanation:
Information provided
[tex]\bar X=52.8[/tex] represent the sample mean for the MPG of the cars
[tex]\sigma=1.6[/tex] represent the population standard deviation
[tex]n=250[/tex] sample size of cars
[tex]\mu_o =52.6[/tex] represent the value that we want to test
[tex]\alpha=0.05[/tex] represent the significance level for the hypothesis test.
z would represent the statistic (variable of interest)
[tex]p_v[/tex] represent the p value for the test
Hypothesis
We need to conduct a hypothesis in order to check if the true mean of MPG is different from 52.6 MPG, the system of hypothesis would be:
Null hypothesis:[tex]\mu = 52.6[/tex]
Alternative hypothesis:[tex]\mu \neq 52.6[/tex]
Since we know the population deviation the statistic is given by:
[tex]z=\frac{\bar X-\mu_o}{\frac{\sigma}{\sqrt{n}}}[/tex] (1)
Calculate the statistic
Replacing we have this:
[tex]z=\frac{52.8-52.6}{\frac{1.6}{\sqrt{250}}}=1.976[/tex]
Decision
Since is a two tailed test the p value would be:
[tex]p_v =2*P(z>1.976)=0.0482[/tex]
Since the p value is lower than the significance level wedon't have enough evidence to conclude that the true mean is significantly different from 52.6 MPG.