The calculations for a factorial experiment involving four levels of factor A, three levels of factor B, and three replications resulted in the following data: SST = 275, SSA = 24, SSB = 21, SSAB = 175. Set up the ANOVA table and test for significance using a = 0.05. Show entries to 2 decimals, if necessary. If the answer is zero, enter "0". Use unrounded intermediate values for calculation. Source of Variation Factor A Factor B Interaction Error Total Sum of Squares Degrees of Freedom Mean Square × F value × X p-value

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The calculations for a factorial experiment involving four levels of factor A, three levels of factor B, and three replications resulted in the following data:
SST = 275, SSA = 24, SSB = 21, SSAB = 175. Set up the ANOVA table and test for significance using a = 0.05. Show entries to 2 decimals, if
necessary. If the answer is zero, enter "0". Use unrounded intermediate values for calculation.
Source
of Variation
Factor A
Factor B
Interaction
Error
Total
Sum
of Squares
Degrees
of Freedom
Mean
Square
***
F value
xx
p-value
X X
Transcribed Image Text:The calculations for a factorial experiment involving four levels of factor A, three levels of factor B, and three replications resulted in the following data: SST = 275, SSA = 24, SSB = 21, SSAB = 175. Set up the ANOVA table and test for significance using a = 0.05. Show entries to 2 decimals, if necessary. If the answer is zero, enter "0". Use unrounded intermediate values for calculation. Source of Variation Factor A Factor B Interaction Error Total Sum of Squares Degrees of Freedom Mean Square *** F value xx p-value X X
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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 a = 0.05. Factor A is method of loading and unloading; Factor B is the type of ride.
Factor A
56
52
48
48
48
50
44
46
Set up the ANOVA table (to whole number, but p-value to 4 decimals and F value to 2 decimal, if necessary). Do not round intermediate calculations.
Factor B
Interaction
Source of Variation Sum of Squares Degrees of Freedom Mean Square
Error
Total
24
21
175
Method 1
55
275
Method 2
3
2
6
Roller Coaster
24
35
>
46
48
51
53
X
8
10.5
29.17
Type of Ride
Screaming Demon
2.29
F
3.49
4.59
12.74
p-value
.0312
Long Flume
.0205
0
Transcribed Image Text: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 a = 0.05. Factor A is method of loading and unloading; Factor B is the type of ride. Factor A 56 52 48 48 48 50 44 46 Set up the ANOVA table (to whole number, but p-value to 4 decimals and F value to 2 decimal, if necessary). Do not round intermediate calculations. Factor B Interaction Source of Variation Sum of Squares Degrees of Freedom Mean Square Error Total 24 21 175 Method 1 55 275 Method 2 3 2 6 Roller Coaster 24 35 > 46 48 51 53 X 8 10.5 29.17 Type of Ride Screaming Demon 2.29 F 3.49 4.59 12.74 p-value .0312 Long Flume .0205 0
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