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. Round the slope and y-intercept to the nearest thousandth. Then determine if the regression equation is appropriate for making predictions at the 0.01 level of significance. Critical Values of the Pearson Correlation Coefficient Average Temperatures and Snow Accumulations Average Temperature (℉) 42 27 22 39 44 21 27 18 32 36 Snow Accumulation (in.) 6 11 22 8 12 27 27 20 12 6
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. Round the slope and y-intercept to the nearest thousandth. Then determine if the regression equation is appropriate for making predictions at the 0.01 level of significance. Critical Values of the Pearson Correlation Coefficient Average Temperatures and Snow Accumulations Average Temperature (℉) 42 27 22 39 44 21 27 18 32 36 Snow Accumulation (in.) 6 11 22 8 12 27 27 20 12 6
Chapter4: Linear Functions
Section: Chapter Questions
Problem 30PT: For the following exercises, use Table 4 which shows the percent of unemployed persons 25 years or...
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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. Round the slope and y-intercept to the nearest thousandth. Then determine if the regression equation is appropriate for making predictions at the 0.01 level of significance.
Critical Values of the Pearson
Average Temperatures and Snow Accumulations
Average Temperature (℉) | 42 | 27 | 22 | 39 | 44 | 21 | 27 | 18 | 32 | 36 |
---|---|---|---|---|---|---|---|---|---|---|
Snow Accumulation (in.) | 6 | 11 | 22 | 8 | 12 | 27 | 27 | 20 | 12 | 6 |
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