Answer:
a. linear regression.
Explanation:
Based on the information provided within the question it can be said that in this scenario the best choice would be a linear regression model. That is because this type of approach deals with seeing to what extent there exists a relationship between two variables. Which in this case would be the quantitative data/prices and the square footage of the home.
Answer:
$21,767.50
Explanation:
<u>Computation table:</u>
<u>Particular Amount</u>
Sales $50,000
Less: Costs $23,000
<u>Less: Depreciation $2,250</u>
<u>EBIT $24,750</u>
<u>Less: Interest $2,000.
</u>
<u>EBT $22,750</u>
<u>Less: Tax (23%) $5,232.50
</u>
<u>Net Income $17,517.50</u>
$24,750 + 2,250 -5,232.50
$21,767.50
Not sure but I'll take a chance: Probably product existance. If not then product capture
It is called A COST DRIVER. A cost driver refers to any factor that causes a change in the cost of an activity. Cost driver is used to assign overhead costs to the quantity of a particular goods that is manufactured. Example of a cost driver is direct labour hours input into a production operation.
Answer:
THEIR FACTOR OF PRODUCTIVITY will increase.