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Chapter 10

PSYB01 Textbook Notes - Chapter 10

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Anna Nagy

Chapter 10 Complex Experimental Design Increasing the Number of Levels of an Independent Variable In the simplest experimental design there are only two levels of the independent variable However, a researcher may want to design an experiment with three or more levels for several reasons: 1. A design with only two levels cannot provide very much info about the exact relationship. Eg look at example 10.1 on page 187. It illustrates how a relationship can go from a positive linear relationship to a monotonic positive relationship by adding levels. 2. an experimental design with only two levels of the independent variable cannot detect curvilinear relationships (recall form chapter 4 in a curvilinear relationship the relationship between variables changes and sot he graph changes direction at least once). If a curvilinear relationship is predicted, at least three levels must be used. For example, the relationship between fear arousal and performance may such relationship exist in psychology! 3. Researchers are often interested in comparing more than two groups. For example, when comparing the effect of playing with animals on elderly people, they may want to test the difference between playing with a dog, playing with a cat, playing with a bird, or playing with no animal at all. Increasing the Number of Independent Variables: Factorial Designs Researchers often more than one independent variable in a single experiment, - typically 2 or 3 independent variables are operating simultaneously, which is a closer approximation of real-world conditions in which independent variables do not exist by themselves In any given situation a number of variables are operating to affect behaviour eg the experiment in which both the crowding and the windows were effecting the cognitive performance of participants It is possible to design an experiment with more than one independent variable Factorial Designs are designs with more than one independent variable or factor In a factorial design, all levels of each independent variable are combined with all levels of the other independent variables In the simplest factorial design, known as a 2 x 2 (two by two) factorial design there are two independent variables each with two levels In a study by Ellesworth, a 2 x 2 design was used. They studied the effects of asking misleading questions on the accuracy of eyewitness testimony. The second independent variable was the questioners knowledge of the crime: either they were knowledgeable or nave. This 2 x 2 design resulted in 4 experimental conditions: www.notesolution.com
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