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,ŷ = bo + b₁x. Round the slope and y-intercept to the nearest thousandth. Then determine if the regression equation is appropriate for making predictions at the 0.05 level of significance. Critical Values of the Pearson Correlation Coefficient Average Temperatures and Snow Accumulations Average Temperature (°F) 42 31 24 45 38 18 33 Snow Accumulation (in.) 9 12 27 7 15 22 30 21 13 20 25 37 8

College Algebra
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ISBN:9781938168383
Author:Jay Abramson
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Chapter4: Linear Functions
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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, ŷ = bo + b₁x. Round the slope and y-intercept to the nearest thousandth. Then determine if the regression equation is appropriate for making
predictions at the 0.05 level of significance.
Critical Values of the Pearson Correlation Coefficient
Average Temperature (°F)
Average Temperatures and Snow Accumulations
42 31 24 45 38 18 33 21 25
9 12 27 7 15 22 30 13 20
37
Snow Accumulation (in.)
8
Transcribed Image Text: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, ŷ = bo + b₁x. Round the slope and y-intercept to the nearest thousandth. Then determine if the regression equation is appropriate for making predictions at the 0.05 level of significance. Critical Values of the Pearson Correlation Coefficient Average Temperature (°F) Average Temperatures and Snow Accumulations 42 31 24 45 38 18 33 21 25 9 12 27 7 15 22 30 13 20 37 Snow Accumulation (in.) 8
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