Answer:
Correct option is (a)
Explanation:
For any venture to be successful, it starts with a vision or idea. In this case, Greg is confident that he will be able to convince US Car manufacturers to purchase his fuel efficient car even though his friends were doubtful if his product will be accepted by car manufacturers.
He also had a clear vision as his goal was to make US economy energy efficient. Vision is to have a positive outlook regarding future.
It can be inferred that Greg has both vision and confidence
Answer:
Emergency
Explanation:
Always have extra money for problems that arise.
Answer:
Cost of goods sold = $836
Ending inventory = $315
Explanation:
a) Data and Calculations:
Date Description Units Unit Price Balance
Apr. 1 Inventory 12 $45 $540
Apr. 11 Purchase 13 $47 $1,151 ($540 + 13 * $47)
Apr. 14 Sale (18) $100 $315 ($7 * $45)
Sales revenue = $1,800 ($100 * 18)
Cost of goods sold = $836 ($47 * 13 + $45 * 5)
Ending inventory = $315 ($7 * $45)
b) Under the LIFO (Last in, First out) inventory valuation method, it is assumed that goods that were purchased closest to the selling date were the ones to be sold while those purchased earlier remain in inventory.
Answer:
D) Overhead was underapplied by $4,000.
Explanation:
Overhead is underapplied when the actual balance in the manufacturing overhead control account is larger than the balance in the applied manufacturing overhead account.
In this case, the balance of the manufacturing overhead control is $124,000 while the balance of the applied manufacturing overhead account is $120,000. This means that actual overhead costs were $4,000 higher than budgeted.
Answer:
Explanation:
A Supervised learning allows you to collect data or produce a data output from the previous experience while an unsupervised learning you do not need to supervise the model.
A. Deciding whether to issue a loan to an applicant based on demographic and financial data (with reference to a database of similar data on prior customers). - Supervised learning
B. In an online bookstore, making recommendations to customers concerning additional items to buy based on the buying patterns in prior transactions. - Unsupervised learning
c. Identifying a network data packet as dangerous (virus, hacker attack) based on comparison to other packets whose threat status is known - Supervised learning
d. Identifying segments of similar customers. - Unsupervised learning
e. Predicting whether a company will go bankrupt based on comparing its financial data to those of similar bankrupt and nonbankrupt firms. - Supervised learning
f. Estimating the repair time required for an aircraft based on a trouble ticket. - supervised learning
g. Automated sorting of mail by zip code scanning. - Supervised learning
H. Printing of custom discount coupons at the conclusion of a grocery store checkout based on what you just bought and what others have bought previously - Unsupervised learning
