JEBBERZ that link isn't even clickable
Answer:
Net Income 193,000
Non-monetary terms:
Depreciation expense 25,000
amortization expense 10,000
gain on disposal <u> (7,000) </u>
Adjusted Income 221,000
Change in Working Capital:
Increase in A/R (27,000)
Decreasein Inv 17,000
Increase in Prepaid (5,000)
Increase Accrued /P 11,000
Decreasein A/P (6,000)
Change In Working Capital (10,000)
From Operating Activities 211,000
Investing
Sale of Equipment 47,000
Financing
Bonds Issued 60,000
Cash Flow 318,000
Beginning Cash 99,000
Cash Flow 318,000
Ending Cash 417,000
Explanation:
We first remove the non.monetary concetps from the net income.
Then we adjust for the change in working capital which are the incrase and decrease in the current assets and liabilities account
Increase in asset and decrease in liabilities represent cash outflow
while the opposite is true when an asset decrease(convert to cash) or a liablity increase (delay of the payment)
Answer:
Charlotte has the priority to claim Autumn as her dependent even though William covered 70% of her living expenses during the year. In order for a parent to be able to claim a child as a dependent, he/she must live with the child for more than half the year. In this case, since William left the house, Charlotte has preference over claiming Autumn as her dependent (even though William lived with Autumn for 10 months). Also, a parent always has priority over other relatives including a grandparent.
I believe that the answer is D. That he should become knowledgeable about smart ways to save and about car loans
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
