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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)? $

Almost 80% of business owners are clueless about the competition, resulting in a) lost market share and customers. b) needless lawsuits. c) uninspired products. d) lack of perseverance

Kcompany estimates that overhead costs for the next year will be $4,900,000 for indirect labor and $1,000,000 for factory utilities. the company uses direct labor hours as its overhead allocation base. if 100,000 direct labor hours are planned for this next year, what is the company's plantwide overhead rate?