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Thane Company is interested in establishing the relationship between electricity costs and machine hours. Data have been collected and a regression analysis prepared using Excel.
Thane Company is interested in establishing the relationship between electricity costs and machine hours. Data have been collected and a regression analysis prepared using Excel. The monthly data and the regression output follow:
Month | Machine Hours | Electricity Costs | ||
January | 2,800 | $ | 18,550 | |
February | 3,200 | $ | 21,300 | |
March | 2,200 | $ | 13,650 | |
April | 3,400 | $ | 23,300 | |
May | 4,100 | $ | 28,400 | |
June | 3,600 | $ | 22,300 | |
July | 4,400 | $ | 24,900 | |
August | 3,800 | $ | 22,900 | |
September | 2,300 | $ | 15,800 | |
October | 4,000 | $ | 26,300 | |
November | 5,100 | $ | 31,300 | |
December | 4,500 | $ | 27,900 | |
Summary Output | |
Regression Statistics | |
Multiple R | 0.964 |
R Square | 0.930 |
Adjusted R2 | 0.922 |
Standard Error | 1,451.70 |
Observations | 12.00 |
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | |
Intercept | 2,530.90 | 1,835.03 | 1.38 | 0.20 | (1,557.80) | 6,619.59 |
Machine Hours | 5.67 | 0.49 | 11.49 | 0.00 | 4.57 | 6.77 |
The correlation coefficient for the regression equation for electricity costs is:
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