Answer:
$1,088.12
Explanation:
The formula for calculating monthly repayments is as below.
M= P x <u> r </u>
1 − (1+r)−^n
where p is the loan amount = $220,000
r = 4.3per cent or 0.043 % interest rate per year,
on monthly basis r will be 0.043/12=0.00358%
n = 30 year, which is 30 x 12 months= 360 months
M= $220,000 x <u> 0.00358 </u>
1 - (1+0.00358 ) ^ - 360
M=$220,000 x<u> 0.00358 </u>
1- 0.2762
M = $220,000 x (0.00358 /0.7238)
M = $220,000 x 0.0049461
M = 1,088.12
Monthly payments will be $1,088.12
<span>This is true- it is an example of global outsourcing. Global outsourcing is when a company sends jobs to locations across the globe, where they can get away with hiring more workers and paying them less than they would have to in America. They take advantage of the lack of labor laws and human rights.</span>
Calculation of equal amount to deposit each year to get the future amount:
It is given that a manufacturer of triaxial accelerometers wants to have $2,800,000 available 10 years from now. So we can say that Future value is $2,800,000. We are also given that the deposit rate is 6% per year.
In order to find out the equal amount to deposit each year we need to calculate the annuity using the future value of annuity formula as follows;
Annuity = Future value of annuity / FV of $1 annuity
FV of $1 annuity (at 6% rate for 10 years) is 13.18079
Hence,
Annuity =2,800,000 / 13.18079 = 212,430.36
Hence , equal amount to deposit each year is $212,430.36
Answer:
In order to make a decision utilizing a decision tree, you must:___________
b. begin at Time 0 and work towards the most distant point in time.
Explanation:
Decision trees are built up by starting from the present with the overarching objective (goal) in mind. Then, one classifies the information along various branches and leaf nodes, with each branch representing the outcome of an alternative route or a question answered based on the likelihood of the event happening. Each leaf node represents a class label (decision taken after computing all attributes). This structure can be used to predict likely values of data attributes.