In: Statistics and Probability
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 | 46 | 54 | 50 |
48 | 46 | 46 | |
Method 2 | 45 | 54 | 48 |
47 | 50 | 44 |
Set up the ANOVA table (to whole number, but -value to 2 decimals and value to 1 decimal, if necessary).
Source of Variation | Sum of Squares | Degrees of Freedom | Mean Square | -value | |
Factor A | |||||
Factor B | |||||
Interaction | |||||
Error | |||||
Total |
using excel>data>data analysis>Anova with replication
we have
Anova: Two-Factor With Replication | ||||||
SUMMARY | Roller Coaster | Screaming Demon | Long Flume | Total | ||
Method 1 | ||||||
Count | 2 | 2 | 2 | 6 | ||
Sum | 94 | 100 | 96 | 290 | ||
Average | 47 | 50 | 48 | 48.33333 | ||
Variance | 2 | 32 | 8 | 10.26667 | ||
Method 2 | ||||||
Count | 2 | 2 | 2 | 6 | ||
Sum | 92 | 104 | 92 | 288 | ||
Average | 46 | 52 | 46 | 48 | ||
Variance | 2 | 8 | 8 | 13.2 | ||
Total | ||||||
Count | 4 | 4 | 4 | |||
Sum | 186 | 204 | 188 | |||
Average | 46.5 | 51 | 47 | |||
Variance | 1.666667 | 14.66667 | 6.666667 | |||
ANOVA | ||||||
Source of Variation | SS | df | MS | F | P-value | |
Factor A | 0.333333 | 1 | 0.333333 | 0.033333 | 0.861145 | |
Factor B | 48.66667 | 2 | 24.33333 | 2.433333 | 0.168331 | |
Interaction | 8.666667 | 2 | 4.333333 | 0.433333 | 0.667138 | |
Within | 60 | 6 | 10 | |||
Total | 117.6667 | 11 |