Answer:
$3,200 overapplied
Explanation:
The computation of the total underapplied or overapplied factory overhead is shown below:
Given that
Actual total factory overhead costs incurred is $45,400
Now Overhead applied to production
= (Total factory overhead application rate per standard DLH × Standard direct labor hours allowed)
= $2.70 × 18,000
= $48,600
As we can see that the overhead applied amount is more than the actual amount so the overhead cost would be overapplied i.e.
= $48,600 - $45,400
= $3,200 overapplied
Incomplete question. The remaining part reads;
<u>Identify the sales promotion technique based on the given scenario.</u>
Answer:
<u>Loyalty Points to Customers.</u>
Explanation:
An important sales promotion technique that fits well into this technique is the sales promotion technique. This technique involves providing some incentives that motivate your aggrieved customers to reconsider coming back to you.
For example, Tara could offer her customers loyalty points which they can redeem as discounts for every pair of the new style of lightweight running shoe. By so doing, she may be able to regain the trust of her customers.
Answer:
Quantity variance.
Explanation:
The difference between actual and standard cost caused by the difference between the actual quantity and the standard quantity is called the Quantity variance.
For instance, if Tony needs a standard quantity of 50 pounds of iron to construct a burglary, but only used 51 pounds, then the quantity variance is 1 pound of iron.
<em>Hence, the quantity variance is simply the difference between the actual quantity of materials that should be used and the quantity of materials that was used. </em>
1. is credit card
2. is debit card
3. is card
hope this helped!!!
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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