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1

A(n) is used to represent a category variable numerically.
2

is used to search for patterns in your data.
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Using separate columns for data from each of several measures defines (n) .
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When you used a format, you have columns for participant identification, independent variable codes, and values of dependent measures.
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The major advantage of grouped data is .
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Examining individual data makes most sense when you have .
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Usually, your dependent variable is displayed on the of a graph; whereas the independent variable is displayed on the .
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A(n) shows data as a series of bars extending from an axis representing the independent variable.
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A is best used when you have a quantitative independent variable represented on the horizontal axis of a graph.
10

A curve that reaches a certain point and then levels off is said to be .
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A curve that changes direction only once is .
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A frequency distribution is displayed on a graph called a(n) .
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The most frequent score in a distribution is the .
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If your data were normally distributed and measured on at least an interval scale, the measure of center of choice is the .
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The most popular measure of spread is the .
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A correlation coefficient especially designed for use when one of your variables is dichotomous and the other continuous is the .
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The sign of a correlation coefficient tells you something about the of the relationship between variables, whereas its magnitude tells you about the of the relationship.
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If the scores on one measure increase while the scores on a second decrease, then a(n) exists between the two variables.
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An outlying score can affect the magnitude of a correlation coefficient most severely when the correlation is based on .
20

The point-biserial correlation tends to underestimate the degree of relationship between variables because .
21

The amount of error in prediction in a linear regression analysis is given by the .
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In bivariate regression, the difference between an actual and predicted score is called a(n) .
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1 - r2is the formula for the .
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A table that shows the intercorrelations among a set of variables is a(n) .
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is used when you want to look at the relationships among three or more variables simultaneously.





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