Anova Test Paper

ANOVA Test Paper This week Team C is looking to further our knowledge of hypothesis tests by testing for variances and simultaneously comparing the different means of gasoline to conclude if the populations sampled were equal or not. We will test whether the three sample are from populations with equal variances. This type of testing is called analysis of variance or ANOVA (Lind, Marchal, & Wathen, 2004). The ANOVA test can be conducted with the intent of giving families information on where the best places are to travel on vacation based off gas prices, provide consumers more information on gas prices in different areas of the country for cost of living projections, and enable the gas industry to have additional information on regional pricing standards so they can ensure healthy competition. FETCH Express, a delivery service located predominately in the mid west region, would like to expand its business to include a presence on the east coast. The organization is considering three business options; the first involves expanding its growing business to Georgia, the second involves opening a facility located in Maryland, and the third option entails expansion to Florida. The owner of FETCH plans to open a credit account with Quick Trip, BP, or CITGO to satisfy the company’s fuel needs. The executive team will need to know the unleaded gasoline prices for the Quick Trip gas stations in Georgia, the BP gas stations in Maryland, and the CITGO gas stations in Florida. With the data collected the executive team will use a .05 significance level to determine rather or not a difference in the variation among the three locations exists. To do this the team will need to state the null hypothesis. The null hypothesis is that the variances of the three populations are equal. The alternate hypothesis could be that the variances differ (Lind, et al, 2004).
Step 1: State the Null Hypothesis and the Alternate Hypothesis H0: µ1 = µ2 = µ3 H1: The means are not the same.

References: Lind, D., Marchal, W., & Wathen, S. (2004). Statistical Techniques in Business and Economics, 12 e. New York: The McGraw-Hill Companies.