10:56AAwww-awn.aleks.comO REGRESSION AND CORRELATIONPredictions from the least-squares regressio.OC OO DThe managers of an electric utility wish to examine the relationshipbetween temperature and electricity use in the utility's service regionduring the summer months. In particular, the managers wish to be ableto predict total electricity use for a day from the maximum temperaturethat day. The bivariate data below give the maximum temperature (indegrees Fahrenheit) and the electricity use (in thousands of kilowatthours) of electricity generated and sold for a random sample of sixteensummer days. A best-fitting line for the data, obtained from least-squares regression, is given by =53.28 + 3.07.x, in which x denotes themaximum temperature and y denotes the electricity use. This line isshown in the Figure 1 scatter plot.Temperature, x Electricity use, y(in degreesFahrenheit)(in thousands ofkilowatt hours)78.4295.472.5232.100-72.7276.894.5363.437594.8335.635081.6322.032583.2262.976.1292.889.5314.327592.4351.225084.9354.422571.1300.088.3320.998.6381.1Figure 180.8302.697.5306.2Send data to ExcelBased on this information, answer the following:1. Fill in the blank: For these data, values for electricity use that aregreater than the mean of the values for electricity use tend to bepaired with temperature values that aretemperature values.the mean of thegreater than2. According to the regression equation, for an increase of one degreeFahrenheit in temperature, there is a corresponding increase of howmany thousands of kilowatt hours in electricity use?3.073. From the regression equation, what is the predicted electricity use(in thousands of kilowatt hours) when the temperature is 89.5degrees Fahrenheit? (Round your answer to at least one decimalplace.)349 5354. From the regression equation, what is the predicted electricity useCin thousands of kilowatt hours) when the temperature is 96.5degrees Fahrenheit? (Round your answer to at least one decimalplace.)ExplanationCheckO 2021 McGraw-Hill Education. Al Rights Reserved. Terms of Use I Privacy Accessibility place.)4. From the regression equation, what is the predicted electricity use(in thousands of kilowatt hours) when the temperature is 96.5degrees Fahrenheit? (Round your answer to at least one decimalplace.)?

4. The regression equation is y^=53.28+3.07x.

4. From the regression equation, what is the predicted electricity use |(in thousands of kilowatt hours) when the temperature is 96.5 degrees Fahrenheit? (Round your answer to at least one decimal place.)

4. From the regression equation, what is the predicted electricity use |(in thousands of kilowatt hours) when the temperature is 96.5 degrees Fahrenheit? (Round your answer to at least one decimal place.)

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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11:35 AA www-awn.aleks.com O REGRESSION AND CORRELATION Predictions from the least-squares regression line Try again. Shasia v Try Again Your answer is incorrect. • Your answer to number 3 is incorrect. The managers of an electric utility wish to examine the relationship between temperature and electricity use in the utility's service region during the summer months. In particular, the managers wish to be able to predict total electricity use for a day from the maximum temperature that day. The bivariate data below give the maximum temperature (in degrees Fahrenheit) and the electricity use (in thousands of kilowatt hours) of electricity generated and sold for a random sample of sixteen summer days. A best-fitting line for the data, obtained from least- squares regression, is given by -53.28 + 3.07x, in which x denotes the maximum temperature and y denotes the electricity use. This line is shown in the Figure 1 scatter plot. Temperature, x Electricity use, y (in degrees Fahrenheit) (in…
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