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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. The monthly data and the regression output follow:


Month Machine Hours Electricity Costs
January 2,300 $ 19,100
February 2,700 $ 22,400
March 1,700 $ 14,200
April 2,900 $ 24,400
May 3,600 $ 28,950
June 3,100 $ 23,400
July 3,900 $ 25,450
August 3,300 $ 23,450
September 1,800 $ 16,900
October 3,500 $ 27,400
November 4,500 $ 32,400
December 4,000 $ 28,450


Summary Output
Regression Statistics
Multiple R 0.957
R Square 0.917
Adjusted R2 0.908
Standard Error 1,586.26
Observations 12.00


Coefficients Standard Error t Stat P-value Lower 95% Upper 95%
Intercept 5,970.52 1,766.77 3.38 0.01 2,033.90 9,907.13
Machine Hours 5.76 0.55 10.49 0.00 4.54 6.98

The percent of the total variance that can be explained by the regression is:

Thane Company is interested in establishing the relationship between electricity costs and machine hours Data have been collected and a regression analysis prep class=

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Answer:

0.924

Step-by-step explanation:

R² = 0.854

R = √0.854

R = 0.924

Hence, the correlation Coefficient of electricity tarrif is 0.924 ; this correlation Coefficient value, depicts a strong positive correlation between machine hours and cost of electricity. And can he interpreted to mean that ; Electricity tarrif increases as machine hours increases and also decreases as machine hours decreases.

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