An important application of regression analysis is in the estimation of cost. By collecting data on volume and cost and using the least squares method to develop an estimated regression equation relating volume and cost, one can estimate the cost associated with a particular manufacturing volume. Consider the following sample of monthly production volumes and total costs data for a manufacturing operation for the year 2018. Month (Year 2018) Production Volume (units) Total Costs ($) January 500 6,000 February 350 4,000 March 450 5,000 April 550 5,400 May  600 5.900 June 400 4,000 July 400 4,200 August 350 3,900 September 400 4,300 October 600 6,000 November 700 6,400 December 750 7,000 3. Which of the following is NOT necessarily true about the interpretation of the value of b in the simple linear regression equation y = a + bx for this problem? I. The monthly total costs will increase by $7.6437 for every one-unit increase in the production volume. II. Since b > 0, there is a direct relationship between production volume and total costs. III. Because b > 1, there is a very strong positive linear relationship between production volume and total costs. A. i and ii only B. ii only C. iii only D. ii and iii only  4. Which of the following statements are true about the dependent (or response) and independent (or predictor) variables for the simple linear model in this problem? I. Production volume is dependent on total costs. II. The predictor and response variables are the production volume and total costs, respectively. III. The total costs can be projected using the simple linear regression equation if the production volume is known. A. i and ii only B. i and iii only C. ii and iii only D. i, ii, and iii 5. Calculate the (Pearson) correlation coefficient between production volume and total costs in this problem. A. 0.8391 B. 0.9571 C. 0.9160 D. 0.9783

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FOR 3-8: An important application of regression analysis is in the estimation of cost. By collecting data on volume and cost and using the least squares method to develop an estimated regression equation relating volume and cost, one can estimate the cost associated with a particular manufacturing volume. Consider the following sample of monthly production volumes and total costs data for a manufacturing operation for the year 2018.

Month (Year 2018) Production Volume (units) Total Costs ($)
January 500 6,000
February 350 4,000
March 450

5,000

April 550 5,400
May  600 5.900
June 400 4,000
July 400 4,200
August 350 3,900
September 400 4,300
October 600 6,000
November 700 6,400
December 750 7,000

3. Which of the following is NOT necessarily true about the interpretation of the value of b in the simple linear regression equation y = a + bx for this problem?

I. The monthly total costs will increase by $7.6437 for every one-unit increase in the production volume.

II. Since b > 0, there is a direct relationship between production volume and total costs.

III. Because b > 1, there is a very strong positive linear relationship between production volume and total costs.

A. i and ii only

B. ii only

C. iii only

D. ii and iii only

 4. Which of the following statements are true about the dependent (or response) and independent (or predictor) variables for the simple linear model in this problem?

I. Production volume is dependent on total costs.

II. The predictor and response variables are the production volume and total costs, respectively.

III. The total costs can be projected using the simple linear regression equation if the production volume is known.

A. i and ii only

B. i and iii only

C. ii and iii only

D. i, ii, and iii

5. Calculate the (Pearson) correlation coefficient between production volume and total costs in this problem.

A. 0.8391

B. 0.9571

C. 0.9160

D. 0.9783 

6. Which of the following is the most suitable interpretation of the (Pearson) correlation coefficient between production volume and total costs in this problem?

A. There is a perfect positive correlation between production volume and total costs.

B. There is a very strong positive correlation between production volume and total costs.

C. There is a strong positive correlation between production volume and total costs.

D. There is a positive correlation between production volume and total costs. 

7. The equation of the regression line is given by

A. ? = −116.01 + 0.12?

B. ? = 1321.32 − 7.64?

C. ? = 116.01 + 0.12?

D. ? = 7.64? + 1321.32 

8. How much is the estimated total costs if the corresponding production volume for a particular month is 300 units?

A. $274.80

B. $287.13

C. $2,293.11

D. $3,614.43

 

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