Answer:
$1,050,000
Explanation:
The computation of the net income is shown below:
Net income = Sales revenue × profit margin percentage
= $17,500,000 × 6%
= $1,050,000
To determine the net income we multiplied the sales revenues by its profit margin percentage so that the correct value could be arrived.
Answer:
It is more profitable to continue processing the units.
Explanation:
Giving the following information:
Product A:
Units= 23,000
Selling price= $420,000
Continue processing:
Product B= 6,000 units sold for $106 each
Product C= 11,900 units sold for $52 each
Total cost= $280,000
We need to calculate the effect on the income of both options and choose the most profitable on<u>e. We will not take into account the first costs of Product A because they are irrelevant.</u>
Option 1:
Effect on income= $420,000
Option 2:
Effect on income= (6,000*106) + (11,900*52) - 280,000
Effect on income= $974,800
It is more profitable to continue processing the units.
The answer you are looking for is copyright
Answer: $500
Explanation:
Interest for the period = Amount borrowed * Interest rate * 120/360 days
= 15,000 * 10% * 120/360
= $500
Answer:
And we can find this probability using the normal standard distribution table or excel and we got:
Explanation:
Previous concepts
Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".
The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".
Solution to the problem
Let X the random variable that represent the expected return, and for this case we know the distribution for X is given by:
Where and
We are interested on this probability
And the best way to solve this problem is using the normal standard distribution and the z score given by:
If we apply this formula to our probability we got this:
And we can find this probability using the normal standard distribution table or excel and we got: