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An important application of regression analysis in accounting 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, an accountant can estimate the cost associated with a particular manufacturing volume. consider the following sample of production volumes and total cost data for a manufacturing operation. production volume (units) total cost ($) 400 4000 450 5000 550 5400 600 5900 700 6400 750 7000 compute b 1 and b 0 (to 2 decimals if necessary). b 1 b 0 complete the estimated regression equation (to 2 decimals if necessary). = + x what is the variable cost per unit produced (to 1 decimal)? $ compute the coefficient of determination (to 4 decimals). note: report r 2 between 0 and 1. r 2 = what percentage of the variation in total cost can be explained by the production volume (to 2 decimals)? % the company's production schedule shows 500 units must be produced next month. what is the estimated total cost for this operation (to 2 decimals)? $

Calculate the required rate of return for climax inc., assuming that (1) investors expect a 4.0% rate of inflation in the future, (2) the real risk-free rate is 3.0%, (3) the market risk premium is 5.0%, (4) the firm has a beta of 2.30, and (5) its realized rate of return has averaged 15.0% over the last 5 years. do not round your intermediate calculations.

At the beginning of 2014, winston corporation issued 10% bonds with a face value of $2,000,000. these bonds mature in five years, and interest is paid semiannually on june 30 and december 31. the bonds were sold for $1,852,800 to yield 12%. winston uses a calendar-year reporting period. using the effective-interest method of amortization, what amount of interest expense should be reported for 2014? (round your answer to the nearest dollar.)