Answer:
7.83%
Explanation:
This is calculated by using the Gordon growth model (GGM) formula as follows: P = d / (r - g) ……………………………………… (1)
Where;
P = market price of the stock = $24.09
d = next year annual dividend = $1.26 r = cost of equity = ?
g = dividend growth rate = 2.6%, or 0.026
Substituting the values into equation and solve for r, we have:
24.09 = 1.26 / (r - 0.026)
24.09 (r - 0.026) = 1.26
24.09r - 0.62634 = 1.26
24.09r = 1.26 + 0.62634
24.09r = 1.88634
r = 1.88634 / 24.09
r = 0.0783038605230386, or 7.83038605230386%
Rounding to 2 decimal places. we have:
r = 7.83%
Therefore, the correct option is 7.83 percent.
During an EMS run and your partner instructed you and
suggests you to do and write vital signs written differently than of the
original record obtained, it would likely affect the treatment that could be
administered in the patient. The vital signs are basic and yet they are important
in a person’s data for they are a critical data and it is where medical
professionals base their treatment and assessment to the patient. If this is
written differently, not only will affect the treatment but it could also cause
conflicts and there will be consequences to the people who are involved such as
having suspended or fired in their line of work or having to have criminal
charges.
Answer:
a. Acct. receivable % uncollectible Est. uncollectible
1-30 days old $63,000 3% $1,890
31-90 days old $12,000 14% $1,680
> 90 days old $5,000 37% <u>$1,850</u>
Total <u>$5,420</u>
b. Date General journal Debit Credit
Dec 31 Bad debts expenses $5,150
Allowance for doubtful accounts $5,150
($5,420 - $270)
In data mining, finding an affinity of two products to be commonly together in a shopping cart is known as:
<h3>What is Association Rule Mining?</h3>
This refers to the machine based learning method which aims to find similarities between variables in large databases.
With this in mind, we can see that when the affinity of two common products is used such as a shopping cart, in data mining, this is known as the association rule mining.
Read more about data mining here:
brainly.com/question/13954653
I can get you caught up in a lot of lies
