Respuesta :
Answer:
If we compare the p value and a significance level for example [tex]\alpha=0.05[/tex] we see that [tex]p_v>\alpha[/tex] so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, so we can conclude that the lifetime is not signficantly different from 800 hours.
Step-by-step explanation:
Data given and notation
[tex]\bar X=788[/tex] represent the average life for the sample
[tex]\sigma=40[/tex] represent the population standard deviation
[tex]n=30[/tex] sample size
[tex]\mu_o =800[/tex] represent the value that we want to test
[tex]\alpha[/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 (variable of interest)
State the null and alternative hypotheses.
We need to apply a two tailed test.
What are H0 and Ha for this study?
Null hypothesis: [tex]\mu = 800[/tex]
Alternative hypothesis :[tex]\mu \neq 800[/tex]
Compute the test statistic
The statistic for this case is given by:
[tex]z=\frac{\bar X-\mu_o}{\frac{\sigma}{\sqrt{n}}}[/tex] (1)
z-test: "Is used to compare group means. Is one of the most common tests and is used to determine if the mean is (higher, less or not equal) to an specified value".
Calculate the statistic
We can replace in formula (1) the info given like this:
[tex]z=\frac{788-800}{\frac{40}{\sqrt{30}}}=-1.64[/tex]
Give the appropriate conclusion for the test
Since is a one side left tailed test the p value would be:
[tex]p_v =2*P(z<-1.64)=0.101[/tex]
Conclusion
If we compare the p value and a significance level for example [tex]\alpha=0.05[/tex] we see that [tex]p_v>\alpha[/tex] so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, so we can conclude that the lifetime is not signficantly different from 800 hours.
