The following table gives the data for the average temperature and the snow accumulation in several small towns for a single month. Determine the equation of the regression line, yˆ=b0+b1x�^=�0+�1�. Round the slope and y-intercept to the nearest thousandth. Then determine if the regression equation is appropriate for making predictions at the 0.050.05 level of significance. Critical Values of the Pearson Correlation Coefficient Average Temperatures and Snow Accumulations Average Temperature (℉℉) 3939 2525 1515 4242 4242 2424 3232 2020 3030 3737 Snow Accumulation (in.in.) 66 1515 2929 66 1414 2626 2323 1212 1616 77 Copy Data             Regression equation: yˆ=�^=       Is the equation appropriate? Yes

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The following table gives the data for the average temperature and the snow accumulation in several small towns for a single month. Determine the equation of the regression line, yˆ=b0+b1x�^=�0+�1�. Round the slope and y-intercept to the nearest thousandth. Then determine if the regression equation is appropriate for making predictions at the 0.050.05 level of significance.

Critical Values of the Pearson Correlation Coefficient

Average Temperatures and Snow Accumulations
Average Temperature (℉℉) 3939 2525 1515 4242 4242 2424 3232 2020 3030 3737
Snow Accumulation (in.in.) 66 1515 2929 66 1414 2626 2323 1212 1616 77

Copy Data

 
 
 
 
 
 
Regression equation: yˆ=�^= 
 
 
 Is the equation appropriate? Yes 
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