Answer:
a) Null hypothesis:
Alternative hypothesis:
b) Since we are conducting a left tailed test we need to find a quantile in the normal distribution who accumulates 0.1 of the area in the left and we got:
If the calculated value is lower than -1.28 we have enough evidence to reject the null hypothesis.
c)
d) Since the calculated value is lower than the critical value we have enough evidence to reject the null hypothesis at the significance level of 10%. So then the true mean is significantly lower than 30000 for this case.
Step-by-step explanation:
Data given and notation
For this case we have the following data:
29.1 28.5 28.8 29.4 29.8 29.8 30.1 30.6
We can calculate the mean and deviation with these formulas:
represent the sample mean
represent the sample standard deviation
sample size
represent the value that we want to test
represent the significance level for the hypothesis test.
t would represent the statistic (variable of interest)
represent the p value for the test (variable of interest)
Part a: State the null and alternative hypotheses.
We need to conduct a hypothesis in order to check if the true mean is less than 30000, the system of hypothesis would be:
Null hypothesis:
Alternative hypothesis:
Part b
Since we are conducting a left tailed test we need to find a quantile in the normal distribution who accumulates 0.1 of the area in the left and we got:
If the calculated value is lower than -1.28 we have enough evidence to reject the null hypothesis.
Part c
The statistic is given by:
(1)
We can replace in formula (1) the info given like this:
Part d
Since the calculated value is lower than the critical value we have enough evidence to reject the null hypothesis at the significance level of 10%. So then the true mean is significantly lower than 30000 for this case.