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nrod1120 nrod1120
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3 weeks ago
Use the following to answer the questions below:

A small university is concerned with monitoring the electricity usage in its Student Center, and its officials want to better understand what influences the amount of electricity used on a given day. They collected data on the amount of electricity used in the Student Center each day and the daily high temperature for nearly a year. They also made note of whether each day was a weekend or not (1 = Saturday/Sunday and 0 = Monday - Friday). Regression output is provided.

Helpful notes: 1) Electricity usage is measured in kilowatt hours, 2) During the cold months, the Student Center is heated by gas, not electricity, and 3) Air conditioning the building during the warm months does use electricity.

The regression equation is Electricity = 83.6 + 0.529 High Temp - 25.2 Weekend

PredictorCoefSE CoefTP
Constant83.5604.23819.720.000
High Temp 0.529180.070207.540.000
Weekend-25.1683.724 -6.76 0.000
S = 29.8162   R-Sq = 24.7%   R-Sq(adj) = 24.2%

Analysis of Variance

SourceDFSSMSFP
Regression2904814524150.890.000
Residual Error310275592889
Total312366073

A histogram of the residuals and a scatterplot of the residuals versus the predicted values are provided. Discuss whether the conditions for a multiple linear regression are reasonable by referring to the appropriate plots.

A histogram depicts the results of the conditions for a multiple linear regression. The horizontal axis is labeled, Residuals and has markings from negative 90 to 120 in increments of 30. The vertical axis is labeled, frequency and ranges from 0 to 60 in increments of 10. The plotted bars are approximately bell-shaped. From negative 90 to 90, the bars extend up to counts, 1, 1, 6, 15, 18, 24, 30, 20, 43, 60, 45, 18, 13, 6, 5, 2, 0, and 1.. There is a bar with count, 1 at the interval of negative 100 and negative 90; 110 and 120. All values are approximate.
A scatterplot with a regression line shows the relationship between predicted electricity and residual. The horizontal axis is labeled, Predicted Electricity and has markings from 50 to 140 in increments of 10. The vertical axis is labeled, Residual and has markings from negative 100 to 100 in increments of 50. The regression line starts from (49, 0), extends horizontally to the right, and ends at (141, 0). The dots are densely scattered throughout the regression line, such that a few dots lie above the regression line, a few dots lie below the regression line, and a few dots lie on the regression line. The dots are plotted between the points, 58 to 135 on the horizontal axis and between the points, negative 100 to 120 on the vertical axis. The concentration of the dots is more between the points 92 and 135 on the horizontal axis and between the points, negative 50 and 50 on the vertical axis. An outlier lie is at the point, (104, 120). All values are approximate.
Textbook 
Statistics: Unlocking the Power of Data

Statistics: Unlocking the Power of Data


Edition: 3rd
Authors:
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kamarie3kamarie3
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nrod1120 Author
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3 weeks ago
Good timing, thanks!
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Yesterday
Thanks
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2 hours ago
Thanks for your help!!
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