Exam 10: Determining How Costs Behave

High Tech Manufacturing Inc., incurred total indirect manufacturing labor costs of $480,000. The company is labor intensive. Total labor hours during the period were 5,000. Using qualitative analysis, the manager and the management accountant determine that over the period the indirect manufacturing labor costs are mixed costs with only one cost driver-labor-hours. They separated the total indirect manufacturing labor costs into costs that are fixed ($140,000 based on 8,500 hours of labor) and costs that are variable ($340,000) based on the number of labor-hours used. The company has estimated 7,400 labor hours during the next period. What will be the variable cost per hour?

Simple regression analysis estimates the relationship between the dependent variable and one independent variable.

A linear cost function can only represent fixed cost behavior.

A step cost function is an example of a linear cost function.

Which of the following represents cross-sectional data?

Two common forms of quantitative analysis methods of cost estimation are the high-low method and regression analysis.

Nonlinear cost functions can result because of learning curves.

What are the two assumptions behind a simple linear cost function? Briefly explain the three ways that a linear cost function may behave?

Which of the following is an example of time-series data:

Yancy Company manufactures chairs. Because the efforts of manufacturing are approximately equal between labor and machinery, management is considering other possible cost drivers. By considering different cost drivers, it is anticipated that the estimating process can be improved. The following cost estimating equations with their r² values have been determined for 2017: Required: a.Which equation should be selected for the analysis? b.What other factors should be included in the selection of the estimating equation?

Which of the following is not true about the cause-and-effect criterion when estimating a cost function?

Multicollinearity exists in multiple regression when two or more independent variables are highly correlated with each other.