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------------------------------------------------ Match the linear correlation coefficient to the scatter diagram. The scales on the x-axis and y-axis are the same for each scatter diagram:

(a) \( r = 0.946 \)

(b) \( r = 0.787 \)

(c) \( r = 1 \)

- Scatter diagram for (a)
- Scatter diagram for (b)
- Scatter diagram for (c)

The linear correlation coefficients are matched to their respective scatter diagrams as follows: (a) Scatter diagram L with r=0.946, (b) Scatter diagram Explanatory 1 with r=0.787, and (c) Scatter diagram Explanatory with r=1.

The linear correlation coefficient, denoted as r, measures the strength and direction of the linear relationship between two variables in a scatter diagram. The values of r range from -1 to 1, where a value of -1 indicates a perfect negative linear relationship, 1 indicates a perfect positive linear relationship, and 0 indicates no linear relationship.

In this case, scatter diagram L has a linear correlation coefficient of r=0.946, indicating a strong positive linear relationship between the variables represented on the x and y axes. Scatter diagram Explanatory 1 has a linear correlation coefficient of r=0.787, suggesting a moderate positive linear relationship between the variables. Lastly, scatter diagram Explanatory has a linear correlation coefficient of r=1, indicating a perfect positive linear relationship between the variables.

By matching the linear correlation coefficients to their respective scatter diagrams, we can interpret the strength and direction of the linear relationships observed in the data.

Learn more about correlation coefficients here:
brainly.com/question/28898177

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