\begin{tabular}{|r|r|} \hline Production Volume (units) & Total Cost (\$) \\ \hline 400 & 4300 \\ \hline 450 & 5300 \\ \hline 550 & 5700 \\ \hline 600 & 6200 \\ \hline 700 & 6700 \\ \hline 750 & 7300 \\ \hline \end{tabular} Production Target Est. Cost (\$) 500 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 manufacturing volume. In the Microsoft Excel Online file below you will find a sample of production volumes and total cost data for a manufacturing operation. Conduct a regression analysis to explore the relationship between total cost and production volume and then answer the questions that followion Due to a recent change by Microsoft you will need to open the XLMiner Analysis ToolPak add-in manually from the home ribbon. Open spreadsheet a. Compute b1 and b0 (to 1 decimal). b1 b0 Complete the estimated regression equation (to 1 decimal). y^=+x b. According to this model, what is the change in cost (in dollars) for every unit produced (to 1 decimal)? c. Compute the coefficient of determination (to 3 decimals). Note: report r2 between 0 and 1 . r2= b1 b0 Complete the estimated regression equation (to 1 decimal). y^=+x b. According to this model, what is the change in cost (in dollars) for every unit produced (to 1 decimal)? c. Compute the coefficient of determination (to 3 decimals). Note: report r2 between 0 and 1. r2= What percentage of the variation in total cost can be explained by the production volume (to 1 decimal)? % d. The company's production schedule shows 500 units must be produced next month. What is the estimated total cost for this operation (to the nearest whole number)? $ \begin{tabular}{|r|r|} \hline Production Volume (units) & Total Cost (\$) \\ \hline 400 & 4300 \\ \hline 450 & 5300 \\ \hline 550 & 5700 \\ \hline 600 & 6200 \\ \hline 700 & 6700 \\ \hline 750 & 7300 \\ \hline \end{tabular} Production Target Est. Cost (\$) 500 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 manufacturing volume. In the Microsoft Excel Online file below you will find a sample of production volumes and total cost data for a manufacturing operation. Conduct a regression analysis to explore the relationship between total cost and production volume and then answer the questions that followion Due to a recent change by Microsoft you will need to open the XLMiner Analysis ToolPak add-in manually from the home ribbon. Open spreadsheet a. Compute b1 and b0 (to 1 decimal). b1 b0 Complete the estimated regression equation (to 1 decimal). y^=+x b. According to this model, what is the change in cost (in dollars) for every unit produced (to 1 decimal)? c. Compute the coefficient of determination (to 3 decimals). Note: report r2 between 0 and 1 . r2= b1 b0 Complete the estimated regression equation (to 1 decimal). y^=+x b. According to this model, what is the change in cost (in dollars) for every unit produced (to 1 decimal)? c. Compute the coefficient of determination (to 3 decimals). Note: report r2 between 0 and 1. r2= What percentage of the variation in total cost can be explained by the production volume (to 1 decimal)? % d. The company's production schedule shows 500 units must be produced next month. What is the estimated total cost for this operation (to the nearest whole number)? $
