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2. You are interested in finding out the linear regression fit of 2 sets of variables. You already have the means and standard deviations of both and you have the correlation coefficient. Set up the formulas and find what is necessary for the linear regression equation. Remember: a is rounded to tenth place and b is rounded to ten-thousandth place. The predictor: = 42.5 and Sx = 14.9. The predicted: = 67.3 and sy3 28.0. Correlation coefficient is 0.6552. Regression equation

2. You are interested in finding out the linear regression fit of 2 sets of variables. You already have the means and standard deviations of both and you have the correlation coefficient. Set up the formulas and find what is necessary for the linear regression equation. Remember: a is rounded to tenth place and b is rounded to ten-thousandth place. The predictor: = 42.5 and Sx = 14.9. The predicted: = 67.3 and sy3 28.0. Correlation coefficient is 0.6552. Regression equation

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**Linear Regression Analysis** You are interested in finding out the linear regression fit of two sets of variables. You already have the means and standard deviations of both, and you have the correlation coefficient. Set up the formulas and find what is necessary for the linear regression equation. Remember: \( a \) is rounded to the tenth place and \( b \) is rounded to the ten-thousandth place. - **The predictor:** - Mean (\( \overline{x} \)) = 42.5 - Standard deviation (\( s_x \)) = 14.9 - **The predicted:** - Mean (\( \overline{y} \)) = 67.3 - Standard deviation (\( s_y \)) = 28.0 - **Correlation coefficient:** \( r = 0.6552 \) **Regression Equation:** - Slope (\( b \)) = \( r \cdot \frac{s_y}{s_x} \) - Intercept (\( a \)) = \( \overline{y} - b \cdot \overline{x} \) Fill in your calculated values here: **Equation:** Regression equation \[ y = a + bx \]
Transcribed Image Text:**Linear Regression Analysis** You are interested in finding out the linear regression fit of two sets of variables. You already have the means and standard deviations of both, and you have the correlation coefficient. Set up the formulas and find what is necessary for the linear regression equation. Remember: \( a \) is rounded to the tenth place and \( b \) is rounded to the ten-thousandth place. - **The predictor:** - Mean (\( \overline{x} \)) = 42.5 - Standard deviation (\( s_x \)) = 14.9 - **The predicted:** - Mean (\( \overline{y} \)) = 67.3 - Standard deviation (\( s_y \)) = 28.0 - **Correlation coefficient:** \( r = 0.6552 \) **Regression Equation:** - Slope (\( b \)) = \( r \cdot \frac{s_y}{s_x} \) - Intercept (\( a \)) = \( \overline{y} - b \cdot \overline{x} \) Fill in your calculated values here: **Equation:** Regression equation \[ y = a + bx \]
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