costs. The following information is available: Cordell Industries is in the process of analyzing its manufacturing overhead costs. Cordell Industries is not sure if the number of units produced or number of direct labour hours is the best cost driver to use for predicting manufacturing overhea 1 (Click the icon to view the information.) Requirements Requirement 1. Use Excel regression analysis to determine Cordell Industries' manufacturing overhead cost equation using DL hours as the cost driver. (Round your answers to the nearest cent.) y = S $ + x Comment on the R-square. The R-square is (1)- ; therefore projections (2). The estimated manufacturing overhead costs, if 27,000 DL hours are incurred in January, are $ (Round your answer to the nearest cent.) Requirement 2. Use Excel regression analysis to determine Cordell's manufacturing overhead cost equation using number of units produced as the cost driver. (Round your answers to the nearest cent.) y=s x + $ The projected total manufacturing overhead costs, if 5,000 units are produced, are $ Which cost equation is better-this one or the one from Question 1? Why? (Round your answer to the nearest cent.) The R-square is (3). than it was using DL hours as the cost driver. Therefore, the cost equation using (4) - is the more accurate cost equation. Requirement 3. Use Excel regression analysis to determine Cordell Industries' MOH cost equation using number of units produced as the cost driver. This time, remove any potential outliers before performing the regression. Cordell Industries has identified September as a potential outlier. (Round your answers to the nearest cent.) y = $ x+S How does this affect the R-square? The R-square is (5) with the potential outlier removed. The projected total manufacturing overhead costs, if 5,000 units are produced, are $ Requirement 4. In which cost equation do you have the most confidence? Why? We have the most confidence in the cost equation from (6). (Round your answer to the nearest cent.) The R-square value for that equation was the (7)