Chapter 12: Measures of Association

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Flashcards covering correlation, scatterplots, Pearson's r, and regression analysis.

Last updated 4:13 AM on 5/1/25
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16 Terms

1
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What is a scatterplot?

A visual representation of the values of two variables on a case-by-case basis.

2
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What does a linear association in a scatterplot represent?

A straight line relationship between the variables.

3
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What is a positive or direct association?

Where the variables change in the same way; when one increases/decreases, the other does the same.

4
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What is a negative or inverse association?

Where the variables change in opposite ways; when one goes up, the other comes down.

5
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In measuring the strength of an association, what indicates a stronger association?

When the points in the plot are less dispersed.

6
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What is a curvilinear association?

A scatter plot where the pattern of the plot is a curved line.

7
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What is correlation analysis (Pearson's r)?

A measure of the strength and direction of association between two variables.

8
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What is the range of the Pearson's r value?

-1.0 to +1.0

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What does a positive r value indicate?

A positive or direct association exists.

10
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What does a negative r value indicate?

A negative or indirect association exists

11
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What does the magnitude of the correlation mean?

The closer the value gets to 1.0 (either +1.0 or -1.0), the stronger the association.

12
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What is the coefficient of determination?

The amount of variation in one variable attributable to variation in the other variable; symbolized as r².

13
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What is a regression line?

A line that best fits the points in a scatter plot, showing the patterns in the data.

14
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What does the regression equation describe?

The least squares line.

15
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What is the regression equation?

Y' = a + bX, where 'a' is where the line crosses the Y-axis, 'b' is the slope, and 'X' is a given value.

16
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What is ordinary least squares (OLS)?

Ordinary least squares is a method for estimating the parameters in a linear regression model by minimizing the sum of the squared differences between the observed and predicted values.

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