# Question: Multiple Choice Questions 1 The following cost formula for total purchasing

Multiple Choice Questions
1. The following cost formula for total purchasing cost in a factory was developed using monthly data.
Purchasing cost = \$123,800 + (\$15 x Number of purchase orders)
Next month, 2,000 purchase orders are predicted. The total cost predicted for the purchasing department next month
a. Is \$2,000.
b. Is \$153,800.
c. Is \$30,000.
d. Is \$123,800.
e. Cannot be determined from the above formula.
2. An advantage of the high-low method is that it
a. Is subjective.
b. Is objective.
c. Is the most accurate method.
d. Removes outliers.
e. Is descriptive of nonlinear data.
3. Select the independent and dependent variables.
The following six months of data were collected on maintenance cost and the number of machine hours in a factory:
Independent Variable Dependent Variable
a. Maintenance cost .......... Machine hours
b. Machine hours .......... Maintenance cost
c. Maintenance cost ......... Month
d. Machine hours .......... Month
e. Month ............. Maintenance cost
4. Select the correct set of high and low months.
The following six months of data were collected on maintenance cost and the number of machine hours in a factory:
High Low
a. January .......... April
b. January .......... March
c. June ........... March
d. June ........... April
5. An advantage of the scattergraph method is that it
a. Is objective.
b. Is easier to use than the high-low method.
c. Is the most accurate method.
d. Removes outliers.
e. Is descriptive of nonlinear data.
6. The total cost for monthly supervisory cost in a factory is \$4,500. This cost
a. Is strictly variable.
b. Is strictly fixed.
c. Is a mixed cost.
d. Is a step cost.
e. Cannot be determined from this information.
7. In the method of least squares, the coefficient that tells the percentage of variation in the dependent variable that is explained by the independent variable is
a. The intercept term.
b. The x-coefficient.
c. The coefficient of correlation.
d. The coefficient of determination.
e. None of these.

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