MATLAB: An Introduction with Applications
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The following results are from an independent-measures, two-factor study with n=5 participants in each treatment condition. Use a two-factor ANOVA with α=.05 to evaluate the main effects and the interaction.
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- The following data summarize the results from an independent-measures study comparing three treatment conditions. Treatment I II III N = 12 3 5 6 G = 60 5 5 10 ∑X2 = 392 3 1 10 1 5 6 x̅1 = 3 x̅2 = 4 x̅3 = 8 T1 = 12 T2 = 16 T3 =32…arrow_forwardAn 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. Type of Ride Roller Coaster Screaming Demon Long Flume Method 1 49 50 47 51 42 43 Method 2 48 46 47 50 42 43 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. Source of Variation Sum of Squares Degrees of Freedom Mean Square F p-value Factor A Factor B Interaction Error Total The p-value…arrow_forwardThe 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 = 271, SSA = 22, SSB = 24, SSAB = 170. Set up the ANOVA table and test for any significant main effect and may interaction effect. use a= .05.arrow_forward
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