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Analysis of Experimental Designs II: Factorial ANOVA and Statistical Interpretation

An assignment solution covering factorial ANOVA and statistical data interpretation.

Olivia Smith
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WattsSEDU7006-8-41Experimental Designs IIExperimental Designs IIAnalysis of Experimental Designs II: Factorial ANOVA and StatisticalInterpretationJackson (2012) Chapter Exercises#2.A 4 x 6 factorial design has two independent variables; the first with four levels andthe second with six. A 4 x 6 factorial design has 24 conditions.#4.A cell mean represents the average score of participants in a condition, where aspecific value of each independent variable interacts. Main effect means represent the averagescore of participants for a single independent variable, where no interaction with otherindependent variables are considered.#6.In a complete factorial design comparison is made between each level of allindependent variables with each level of every other independent variable. An incompletefactorial design is considered incomplete because comparisons are not made between each levelof all independent variables with each level of every other independent variable; somecomparisons are not made (Jackson, 2012).#8.The number associated with the way of the ANOVA identifies the number ofindependent variables. A two-way ANOVA is an analysis of variance with two independentvariables. A three-way ANOVA is an analysis of variance comparing three independentvariables.#10.

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