Inferential Findings and Statistics
Inferential Findings and Statistics
After finding the descriptive statistics to Team A’s data for SkyNav, it is important to find which test is necessary to run to reject or fail to reject the null hypothesis. Since there are two means involved, EPA Gas and Jet Fuel, it is necessary to run a hypothesis test where we compare two independent groups. By comparing these two means the team will be able to answer the research question and discern which method of fuel is more efficient to utilize to continue running the business. Null hypothesis and alternate hypothesis are stated below:
H0: µ1=µ2
HA: µ1≠µ2
The data used to reject or fail to reject the null hypothesis is shown in Excel attachment (Learning Team A, 2014).
With this data the hypothesis test that will be used is “compare two independent groups”. By running the test with a 95% confidence level we find that our p-value is 0.00 therefore, we reject the null hypothesis and assume that the alternative is true (Learning Team A, 2014). This in turn means that the EPA Gas and Jet Fuel average consumption of gallons per day differ significantly from each other. This leads SkyNav management to believe that there is a significant difference in cost when using one method of fuel over the other.
As a team member, seeking the most cost effective method of fueling, I believe that running another test could answer the research question more accurately. This test would also be with a confidence level of 95% but instead of being two-tailed, it would be one-tailed. Since the EPA Gas sample mean, 36.994, is lower than the Jet Fuel sample mean, 86.61, it is safe to assume a new alternate hypothesis:
H0: µ1=µ2
HA: µ1<µ2
Running this one-tailed test gave