1. Forecast future sales and costs.
Small improvements may be possible, but large improvements are unlikely to occur without significant changes in operations.
2. Describe information bias, cognitive bias, and predisposition bias.
When the quality of information is poor, resulting in data that misestimates or misrepresents a situation, poor decisions are likely to be made. This is called information bias. When people’s minds do not appropriately process information, cognitive biases occur. A predisposition bias occurs when people do not control their preferences, attitudes, or emotions in making a decision and they are therefore unable to make an objective analysis of the situation or problem.
3. Explain why the high-low method might not be a good method for estimating the cost function.
(1) General concern: whether the high point ad low point are outliers
(2) Specific concern: only a few points in data set, relevant range is limited
4. Whether cost function is a good estimate for future forecast.
(1) Historical data
(2) Number of observations
5. Why to create a scatter plot of the data before perform regression analysis.
Costs and potential cost driver data are plotted to determine whether further analysis is necessary. Analysis of the plots involves looking for a linear or football-shaped positive slope or trend. If the observations are widely scattered, the cost driver does not explain the variation in cost; either the driver is wrong or the cost is mostly fixed. Sometimes a cost that is mostly variable. The plots help determine whether regression analysis should be performed using any of the potential drivers.
6. Why the cost per unit under the traditional costing system is different from the cost per unit under the ABC system.
In the traditional costing system, the indirect costs were combined into a single cost pool and then allocated based on direct labor hours used by each order. Direct labor hours may or may not