D Question 39 2.5 pts An electric utility used the following data from prior summer months to forecast monthly residential demand for electricity for next summer. Based on this information, determine the least squares regression line, construct a 95% confidence interval for the slope coefficient and construct a 95% prediction interval for how much electricity a given residence will use in a month when the average temperature is 85 degrees. SSxx = 137.6188, SSyy = 35,095.5000, SSxy = 2,149.6250 temp | kilowatt hours 89.9 | 4,603 91.4 | 4,644 91.5 | 4,626 87.2 | 4,543 90.9 | 4,636 87.9 | 4,565 82.6 | 4,515 98.1 | 4,742 O y-hat = 3,204.4131 + 15.6201X, confidence interval for the slope 12.3024 to 18.938, mean usage 4,487.7120 to 4,576.5390 O y-hat = -192.3824 + 0.0613X, confidence interval for the slope 0.0482 to 0.074, mean usage -189.7620 to -184.5902 O y-hat = 3,204.4131X + 15.6201, confidence interval for the slope 12.3024 to 18.938, mean usage 4,510.7314 to 4,553.5197 O y-hat = 3,204.4131 + 15.6201X, confidence interval for the slope 4,487.7120 to 4,576.539, mean usage 4,510.7314 to 4,553.5197 O y-hat = -192.3824X + 0.0613, confidence interval for the slope 0.0482 to 0.074, mean usage -188.0402 to 186.3120 O y-hat = 3,204.4131 + 15.6201X, confidence interval for the slope 12.3024 to 18.938, mean usage 4,510.7314 to 4,553.5197 O y-hat = -192.3824 + 0.0613X, confidence interval for the slope -189.7620 to -184.590, mean usage -188.0402 to -186.3120 O y-hat = -192.3824 + 0.0613X, confidence interval for the slope 0.0482 to 0.074, mean usage -188.0402 to -186.3120