Answer:
a. 4 years
b. 19 years
c. 19 years
d. 25 years
Explanation:
The number of years, n is calculated for each future value as follows :
a. $1,360
Pv = - $1,000
Pmt = $ 0
P/y = 1
r = 8 %
Fv = $1,360
n = ?
Using a Financial Calculator, the number of years, n is 3.9953 or 4 years
b. $2,720
Pv = - $1,000
Pmt = $ 0
P/y = 1
r = 8 %
Fv = $2,720
n = ?
Using a Financial Calculator, the number of years, n is 13.00 or 13 years
c. $4,316
Pv = - $1,000
Pmt = $ 0
P/y = 1
r = 8 %
Fv = $4,316
n = ?
Using a Financial Calculator, the number of years, n is 19.00 or 19 years
d. $6,848
Pv = - $1,000
Pmt = $ 0
P/y = 1
r = 8 %
Fv = $6,848
n = ?
Using a Financial Calculator, the number of years, n is 24.9991 or 25 years
The purchase amount that Icon Co. would record on April 2 would be: <u>c. $4,000</u>.
<h3>What is the purchase amount to be recorded?</h3>
The purchase amount that should be recorded on the date of purchase is the amount of the transaction. This does not take into account the return and discount which happened later.
This implies that Icon Co. will reduce the purchase amount on April 4 when half of the goods were returned with a contra entry. And discount will be based on the balance of $2,000 instead of $4,000.
<h3>Data and Calculations:</h3>
Purchase on April 2 = $4,000
Purchases Return on April 4 = $2,000
Thus, the purchase amount that Icon Co. would record on April 2 would be: <u>c. $4,000</u>.
Learn more about recording credit purchases at brainly.com/question/5651500
Answer:
Option "2" is the correct answer to the following statement.
Explanation:
A short-term loan is a form of loan received to endorse short term business and personal wealth for a very short period. It is a tempting and temporary option, for most of the short term businesses which are not easily eligible for a loan from a financial institution.
This type of loan mostly paid back in a very short period usually in 12 months.
In this case, MVJ gets a loan for 90 days or 3 months so it is considered a short term loan.
Answer:
a. linear regression.
Explanation:
Based on the information provided within the question it can be said that in this scenario the best choice would be a linear regression model. That is because this type of approach deals with seeing to what extent there exists a relationship between two variables. Which in this case would be the quantitative data/prices and the square footage of the home.