The monthly overhead of the pharmacy is <u>$52,875</u>.
<h3>What is the overhead?</h3>
The overhead refers to the costs or expenses for running a business. These expenses cannot be traced to any product or service unit
They tend to be mostly fixed in nature, though, some may exhibit semi-variable characteristics.
Some of the overhead costs include:
Rent
Utilities
Insurance
Office Supplies
Travel expenses
Salaries and wages
Advertising expenses
Accounting and legal expenses.
<h3>Data and Calculations:</h3>
Monthly sales $278,000
Inventory purchases $186,000
<h3>Overhead costs:</h3>
Salaries and wages $49,000
Utilities $2,000
Insurance $1,200
Maintenance $675
Total overhead = $52,875
Thus, the monthly overhead of the pharmacy is <u>$52,875</u>.
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Answer:
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Answer:
3.52 years
Explanation:
In the payback, we analyze in how many years the invested amount is recovered. The computation is shown below:
In year 0 = $1,100
In year 1 = $300
In year 2 = $310
In year 3 = $320
In year 4 = $330
In year 5 = $340
If we sum the first 3 year cash inflows than it would be $930
Now we deduct the $930 from the $1,100 , so the amount would be $170 as if we added the fourth year cash inflow so the total amount exceed to the initial investment. So, we deduct it
And, the next year cash inflow is $320
So, the payback period equal to
= 3 years + ($170 ÷ $330)
= 3.52 years
In 3.52 years, the invested amount is recovered.
Answer:
d.$56,000
Explanation:
For computing the cost of counting, first we have to calculate the total salary amount which is shown below:
Total Salary = Average salary × number of employees
= $35,000 × 4 employees
= $140,000
Now the cost of counting would be equal to
= Total salary × counting percentage
= $140,000 × 0%
= $56,000
Answer: Option D
Explanation: Big data is an area that deals with respects of analyzing, systematically extracting data from or otherwise dealing with sets of data that are far too significant or complicated to be handled by conventional software applications for data management.
We may not test when we handle big data, but simply watch and monitor what is happening. Big data also frequently include data with sizes that surpass conventional software's capacity to process in an appropriate time and cost.
Hence from the above we can conclude that the correct option is D.