Question

In: Statistics and Probability

GENERAL INSTRUCTIONS Data should be analyzed in Excel. Everything should be appropriately labeled. Simple Regression: Examine...

GENERAL INSTRUCTIONS

Data should be analyzed in Excel. Everything should be appropriately labeled.

  1. Simple Regression: Examine the relationship between the number of units produced and the total manufacturing overhead by performing Regression Analysis and generating a “Line-fit” plot. Highlight the following in YELLOW on the spreadsheet:
  1. What is the coefficient of correlation and what does it say about the relationship?
  2. What is the coefficient of determination and what does it say about the relationship?
  3. What is the equation of this line? ( y = mx + b), where Total Cost = (Variable Cost Per Unit * Units) + Total Fixed Cost.
  4. Multiple Regression: Examine the relationship between the number of units produced and the number of production batches and their effect on total manufacturing overhead. What is the coefficient of determination? How did multiple (versus single) regression help/hurt the r-squared?
  5. Break-Even Analysis: Calculate the following, assuming Simple Regression (show work in the Break-Even tab):
    1. What is the average per Unit Direct Materials Cost?
    2. What is the average per Unit Direct Labor Cost?
    3. Assume variable General and Administrative expenses are $12 per unit. What is the total variable cost per unit?
    4. Assume total fixed General and Administrative expenses are $2,000 per month. What is the total fixed cost per month?
    5. Assume sales price per unit is $400. What is the Contribution Margin Per Unit?
    6. What is the Break Even Point in Units?

Solutions

Expert Solution

Given that

1) The data was entered in excel and analysis was performed using 'Data Analysis' toolkit. The regression analysis can be show as follows: flitted line plot obtained is as follows::

a) The correlation coefficient is 0.7255 and it suggests that number of units produced and the total manufacturing overhead are positively correlated with a high magnitude.

b) The coefficient of determination is 0.5264 or 52.64% and it suggests that the model explain approximately 52% of the variability in the data.

c) The equation of the line is as follows:

Units produced=-319.473+0.0402(Manufacturing overhead)


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