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A great deal of psychological research examines the effect a single independent variable has on a single dependent variable. However, it is perfectly reasonable to examine the effects multiple independent variables simultaneously have on a single dependent variable. Experimental designs that include multiple independent variables are known as factorial designs. They come in a wide variety including between-group and within-subject variables and a mixture of both kinds. When two or more variables in a factorial design show a statistically significant interaction, it is common to analyze the simple main effects. Simple main effects analysis typically involves the examination of the effects of one independent variable at different levels of a second independent variable.

Figure 1 The Means and Standard Errors for Different Hint Conditions for Solving the Tower of Hanoi Problem

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Interactions

Suppose an experiment was conducted that examined the consequences of providing different hints for solving the tower of Hanoi problem. The first condition simply provides the rules and the goal for the problem (No hint). The second condition involves telling the participants not to think about moving disks but moving pyramids of disks (Pyramid). The third condition involves telling participants about moving pyramids of disks and states what the first move is (Pyramid + First). The dependent variable is the number of moves to solution of the problem. The results are shown in Figure 1.

These results are explained in terms of reducing the amount of planning that is required. The greater the amount of planning that is necessary, the more mistakes that are made because it is easier to forget long plans.

A different experiment using the tower of Hanoi was also conducted. Three groups were selected according to age: 5–7 years, 9–11 years, and 13–15 years old. Figure 2 shows the results.

The results are also explained with respect to planning such that younger children cannot remember the plans they have made, whereas older children can. In the first experiment, the reduction in planning demands is obtained by changing the representation of the problem. In the second experiment, the ability to deal with planning demands vary according to age. To determine whether reducing the planning demands for younger children by changing the representation of the problem helps them to overcome their problems in planning, the two variables (age and problem representation) are considered at the same time.

Suppose the results shown in Figure 3 were obtained. In this case, the effects of changing the representation of the problem differ with respect to age. In other words, the effects of one variable are different for the different levels of the second variable. This is known as an interaction.

A more formal definition of an interaction is as follows:

Figure 2 The Mean and Standard Errors for Different Ages for Solving the Tower of Hanoi Problem

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Figure 3 The Mean and Standard Errors for the Interaction Between Different Ages and Hint Conditions for Solving the Tower of Hanoi Problem

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Table 1 An Example ANOVA Output

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An interaction is present when the simple effects of one independent variable are not the same at different levels of the second independent variable.

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