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Department
Psychology
Course
PSYC 3000
Professor
Bruce Hutcheon
Semester
Winter

Description
How many different alpha terms exist in the structural model for a 2way design with a3 and b4 3General FeedbackExplanationin this design treatment A has 3 levels At each level there is a different treatment effect alphak which quantifies how much any observation at that level is pushed away from the grand mean solely by virtue being exposed to that level of treatment A Since there are 3 levels there are 3 separate treatment effects alpha1 alpha2 and alpha3How many different beta terms exist in the structural model for a 2way design with a3 and b4 4 General FeedbackExplanationthis is like the previous question except it is asking about the effects associated with treatment B Since there are 4 levels of this treatment there are 4 separate beta termsHow many different alphabeta terms exist in a 2way design with with a3 and b4 12General FeedbackExplanationparticipants in a 3x4 design are exposed to 12 different combinations of the 2 treatmentson in each cell of the design There are therefore 12 different levels of interaction possible and each one needs a separate term alphabetakj to be calculated for itWhich of the following terms are used in calculating the main effect of treatment A for a 2waySquared deviations of marginal means of A from the grand meanGeneral FeedbackExplanationa main effect in a 2way ANOVA tests to see if some set marginal means differ by more than chance from each other To test of the main effect of treatment A we use squared deviations of its marginal means for the grand mean since these are estimates of the alphak terms ie the effects of treatment A in isolation These squared deviations would be summed over all observations in all cells to calculate SSA then divided by the degrees of freedom for treatment A to get MSA and then finally divided by the mean square error to get the F ratio for the testWhich of the following characterizes the alphak terms that appear in the structural model for a 2way design Differences between marginal means for treatment A and the grand meanGeneral FeedbackExplanationthis question is the same as the previous question The previous question asked about the terms needed to calculate the sum of squartes for testing the main efect of treatment a in a 2 way design and this asks about the alphak But these are the same thing So the answer is the same tooWhich of the following characterizes the betaj terms that appear in the structural model for a 2way designDifferences between marginal means for treatment B and the grand mean General FeedbackExplanationthe isolated effects of treatment B are described by the betaj terms in the structural model Each of these betaj terms is a difference between one of the marginal means for B and the grand meanLook at the following table showing the values of the cell means marginal means and grand mean for a design with a2 and b3 What is the value ofthe isolated effect of being exposed to level 1 of treatment A B1B2B3 A181012M110 A2666M26M1 7M2 8M3 9M 82General FeedbackExplanationthe question asks for alpha1 Among all the influences that push individual observations in cell 13 of the design away from the grand mean alpha1 is the push that is due to being exposed to level 1 of treatment A where isolated means we are disregarding any interactions with treatment B This push is measured by the deviation of the marginal mean for level 1 of A from the grand mean Looking at the table this is M1M108 2 For every participant in cell 13 this term will be squared and then added to other similar terms to form SSA Note that all participants in cell 13 have the same value for alpha1 because they are all exposed to level 1 of treatment A In fact every participant at level 1 of the design will contribute this same amount to SSA since every participant at level 1 has the same marginal meanLook at the following table showing the values of the cell means marginal means and grand mean for a design with a2 and b3 What is the value ofthe effect of the interaction between factors A and B for participants in cell 13 of the design 1General FeedbackExplanationthe questions asks for alphabeta13 Of all the influences pushing observations in cell 13 away from the grand mean one of them is the interaction between treatments A and B If there was no interaction between treatments A and B then M13 the mean of all observations
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