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10 - complex experimental designs

10 - complex experimental designs - Increasing the Number...

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Increasing the Number of Levels of an Independent Variable 00:42 A researcher might want to design an experiment with three or more levels for  several reasons A design with only two levels of the independent variable cannot provide very  much information about the exact form of the relationship between the  independent and dependent variables Variables are sometimes related in a curvilinear or nonmonotonic fashion  The direction of relationship changes  Inverted-U: With a wide range of levels of the independent variable, the  relationship would have an inverted U shape  If a curvilinear relationship is predicted, at least three levels must be used  Researchers frequently are interested in comparing more than two groups
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Increasing the Number of Independent Variables: Factorial  Designs 00:42 Researchers often manipulate more than one independent variable in a single  experiment  Two or three independent variables are operating simultaneously  This type of experimental design is a closer approximation of real-world  conditions Factorial designs: Designs with more than one independent variable All levels of each independent variable are combined with all levels of the  other independent variables  Interpretation of Factorial Designs Factorial designs yield two kinds of information  o Main effect: Information about the effect of each independent variable  taken by itself  o Interaction: The effect of one independent variable depends on the  particular level of the other variable  The effect that an independent variable has on the dependent variable  depends on the level of the other independent variable 
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