Question

An amusement park studied methods for decreasing the waiting time (minutes) for rides by loading and unloading riders more efficiently. Two alternative loading/unloading methods have been proposed. To account for potential differences due to the type of ride and the possible interaction between the method of loading and unloading and the type of ride, a factorial experiment was designed. Use the following data to test for any significant effect due to the loading and unloading method, the type of ride, and interaction. Use . Factor A is method of loading and unloading; Factor B is the type of ride.

Type of Ride
	Roller Coaster	Screaming Demon	Long Flume
Method 1	48	53	51
	50	45	47
Method 2	47	54	51
	49	50	47

Set up the ANOVA table (to whole number, but -value to 2 decimals and value to 1 decimal, if necessary). The p-value for Factor A is? What is your conclusion with respect to Factor A? The p-value for Factor B is? What is your conclusion with respect to Factor B? The p-value for the interaction of factors A and B is? What is your conclusion with respect to the interaction of Factors A and B? What is your recommendation to the amusement park?

Answer 1

Using Excel

data -> data analysis -> Anova: Two-Factor With Replication

p-value of Factor A = 0.7275 > alpha

hence we fail to reject the null hypothesis

we conclude that Factor A is not significant

p-value of Factor B = 0.6671 > alpha

hence we fail to reject the null hypothesis

we conclude that Factor B is not significant

p-value of interaction = 0.6671 > alpha

hence we fail to reject the null hypothesis

we conclude that interaction is not significant