ASSIGNMENT
1 Describe the term fixed cost and give several examples of fixed costs within a car rental agency when the cost per car rental is the cost object.
2 Describe the term variable cost and give several examples of variable costs within a car rental agency when the cost per rental is the cost object.
3 Describe the term mixed cost and give several examples of mixed costs within a car rental agency when the cost per rental is the cost object.
4 Why are outliers a problem for any cost estimation technique?
5 “As volume increases, total cost increases and per-unit cost decreases.” What type of linear cost function does this describe? Draw a simple graph of this type of cost function.
6 An automobile assembly plant closes every August to retool for the next year’s model. How should August’s cost data be used in estimating the overhead cost function?
7 Explain why it is important to consider changing circumstances when estimating a cost function.
8 At two levels of activity within the relevant range, average costs are $192 and $188, respectively. Assuming the cost function is linear, what can be said about the existence of fixed and variable costs?
9 List two opportunities you would forgo when you decide to study on a Friday night. List relevant cash flows for those two opportunities. Is it possible to assign a quantitative value to the benefits you receive from either of these two missed
opportunities? Explain.
10 Explain how information from a scatter plot helps in categorizing a cost as fixed, variable, or mixed.
11 Explain the analysis at the account level approach to developing a cost function.
12 In your own words, define sunk costs and describe a decision for which you mistakenly included a sunk cost.
13 Explain why it is often difficult to identify an appropriate, relevant, and reliable measure for estimating a cost function.
14 The trend line developed using regression analysis provides a more accurate representation of a mixed cost function than the two-point or high-low methods. Explain why.
15 Explain why small sample sizes can be a problem when using historical data for estimating a cost function.
