In: Statistics and Probability
QUESTION 5
In a factorial design, a main effect is the
1. |
effect of the interaction between two variables. |
|
2. |
effect of one independent variable at one level of the other independent variable. |
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3. |
effect of one independent variable averaged over the levels of the other independent variable. |
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4. |
only effect of interest |
QUESTION 11
The overall effect of an independent variable ignoring other independent variables is called a(n) ____________.
1. |
collapsed effect |
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2. |
interaction |
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3. |
main effect |
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4. |
omnibus effect |
When graphing the results of a complex design, the dependent variable is always placed
1. |
in the graph itself. |
|
2. |
on the y-axis (vertical). |
|
3. |
on both the x- and y-axes. |
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4. |
on the x-axis (horizontal). |
A study that has more than one independent variable is said to use a factorial design. A “factor” is another name for an independent variable.
A main effect is the effect of one independent variable on the dependent variable—averaging across the levels of the other independent variables i.e. ignoring the effects of all other independent variables. In general, there is one main effect for every independent variable in a study.
There is an interaction effect (or just “interaction”) when the effect of one independent variable depends on the level of another independent variable. The effect of one independent variable can depend on the level of the other in several different ways such as spreading interactions and cross-over interaction.
Now moving on to the QUESTION 5
In a factorial design, a main effect is the -
effect of one independent variable averaged over the levels of the other independent variable [Option 3]
QUESTION 11
The overall effect of an independent variable ignoring other independent variables is called a
main effect [Option 3]
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When graphing the results of a complex design, the dependent variable is always placed
on the y-axis (vertical) [Option 2]
On a 2D graph, the independent variable is typically displayed along the X-axis. The dependent variable is typically on the Y-axis. Most researchers and people believe that it is the convention and it makes things easier for everyone.
If you consider the independent variable as the 'Cause' and the dependent variable as the 'Effect', we prefer to put the effect on the Y-axis because 'cause' is not in our control. We visually think of a timeline as progressing from left to right. But, that is simply a convention. Occasionally, you might have a good reason to break from convention, but otherwise I would suggest that you should stick with it in order to make your work easier to follow.