Accomplished, Achieved, Active in, Awarded, Assisted, Broadened, Built, Chaired, Championed, Completed, Delegated, Distinguished, Enacted, Enhanced, Facilitated, Formulated, Graduated, Granted, Handled, Helped, Implemented, Improved, Increased, Initiated, Joined, Kept, Led, Licensed, Managed, Mastered, Navigated, Netted, Obtained, Outlined, Performed, Placed, Qualified, Received, Recorded, Secured, Served, Taught, Trained, Understudied, Undertook, Verified, Volunteered, Widened, Worked.
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Answer:
Contribution per unit
= Selling price - Variable cost per unit
= $27 -$13
= $14
Contribution margin ratio
= Contribution per unit
selling price
= $14
$27
= 0.518518518
Break-even point in dollars
= $1,400
0.518518518
= $2,700
Explanation:
Break-even point in dollars equals fixed cost divided by contribution margin ratio. Contribution margin ratio is equal to contribution per unit divided by selling price. Contribution per unit is selling price minus variable cost per unit.
Answer:
Mortgage, 20%, 80%
Explanation:
Typically required on Mortgage loans when the down payment is less than 20% and loan-to-value ratio is in excess of 80%. Loans with higher LTVs don't conform to Fannie Mae/Freddie Mac guidelines, so a lender may require PMI to offset the risk.
Answer:
total product costs = $101750
Explanation:
given data
overhead costs = $ 100
Direct materials of $41,000
direct manufacturing labor = 450
per hour = $35
markup rate = 30 %
solution
we get here total product costs that is express as
total product costs = Direct materials + DML + MOH ..........1
total product costs = $41,000 + ( 450 × $35 ) + ( 450 × $100 )
total product costs = $41,000 + $15750 + $45000
total product costs = $101750
None of the above. The Flu Trends model was based on Goo-gle search data.
<h3>Goo-gle Flu Trends and the Power of Big Data</h3>
In 2009, Goo-gle launched a new service called Goo-gle Flu Trends. The service used data from Goo-gle searches to estimate the level of flu activity in different areas of the United States. The results were pretty accurate - in some cases, Goo-gle Flu Trends was able to detect flu outbreaks before government health agencies did.
Goo-gle Flu Trends was a great example of the power of big data. By analyzing a large dataset, Goo-gle was able to find patterns that would have been otherwise undetectable. And because Goo-gle has so much data, its findings were often more accurate than those of government health agencies.
Unfortunately, Goo-gle Flu Trends was discontinued in 2015. But its legacy lives on - other companies are now using big data to detect disease outbreaks, and the field of data science is only getting more important.
Learn more about trends models:
brainly.com/question/15552860
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