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Read the following description of a data set. $\newline$ Charlie and Shawna are judges for the Richmond Ice Staking Federation. Due to claims of malfeasance at recent competitions, a reporter is investigating the relationship between the scores awarded by the two judges.She has collected the scores awarded by Charlie, $x$ , and Shawna, $y$ , for each performance in the last competition.The least squares regression line of this data set is: $y = 0.053x + 4.306$ $\newline$ Complete the following sentence: $\newline$ The least squares regression line predicts an increase of $\_\_$ points in the score Shawna awards for an increase of $1$ point in the score Charlie awards.

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Interpret regression lines

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Q. Read the following description of a data set.

\newline

Charlie and Shawna are judges for the Richmond Ice Staking Federation. Due to claims of malfeasance at recent competitions, a reporter is investigating the relationship between the scores awarded by the two judges.She has collected the scores awarded by Charlie,

x

, and Shawna,

y

, for each performance in the last competition.The least squares regression line of this data set is:

y = 0.053x + 4.306

\newline

Complete the following sentence:

\newline

The least squares regression line predicts an increase of

\_\_

points in the score Shawna awards for an increase of

1

point in the score Charlie awards.

Identify Slope: Identify the slope of the regression line. $\newline$ The slope of the regression line is the coefficient of $x$ in the equation $y = 0.053x + 4.306$ . This coefficient represents the change in $y$ for each unit increase in $x$ .
Interpret Slope: Interpret the slope. $\newline$ The slope of $0.053$ means that for every $1$ point increase in Charlie's score ( $x$ ), Shawna's score ( $y$ ) is predicted to increase by $0.053$ points.
Check for Errors: Check for any mathematical errors. There are no calculations to perform in this step since the slope is given directly in the equation. Therefore, there is no math error.

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