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Unformatted text preview: Factorial Experimental Design 19:20 Factorial experimental designs: Experimental designs with more than one independent (manipulated) variable Factor: Each of the manipulated independent variables Factorial research designs are described with a notational system that concisely indicates both how many factors there are in the design and how many levels there are in each factor Cells: Conditions in a factorial designs The use of more than one independent variable in a single experiment increases the amount of information that can be gained from the experimental design Always cheaper in terms of the number of research participants needed to include two or more factors within a single experiment rather than running separate one-way experiments The factorial design provides all of the information that would be gained from two separate one-way designs, as well as other information that would not have been available if the experiments had been run separately These designs help researchers draw conclusions about the causal effects of the independent variables on the dependent variable The Two-Way Design Factorial designs involve the addition of new independent variables to one- way experiments, often with the goal of finding out whether the original results will hold up in new situations Crossing the factors: The conditions are arranged such that each level of each independent variable occurs with each level of the other independent variables o It is important in factorial designs that the conditions be equated before the manipulations occur Usually accomplished through random assignment of participants to one of the conditions Possible to use repeated-measure factors The research hypothesis in a factorial design normally makes a very specific prediction about the pattern of means that is expected to be observed on the dependent measure Main Effects...
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This note was uploaded on 11/16/2010 for the course PSYC 420 taught by Professor Staff during the Fall '08 term at Maryland.
- Fall '08