Answer:
A speculative risk is uncertain degree of gain or loss. Every speculative risk are made as conscious choices and are not just a result of uncontrollable circumstances.
Explanation:
It's basically a conscious choice you made!
Answer:
$59,080
Explanation:
The calculation of September cash disbursements is shown below:-
September cash disbursement = Company's budgeted fixed manufacturing overhead - Depreciation + Variable manufacturing overhead
= $43,120 - $3,640 + $7.00 × 2,800
= $43,120 - $3,640 + $19,600
= $62,720 - $3,640
= $59,080
Therefore for computing the September cash disbursement we simply applied the above formula.
Answer:
Consumption Function : Relationship between Consumption Spending & Income
Consumption Function Slope = Marginal Propensity Curve (MPC)
Change in Consumption = Change in Income X MPC
Explanation:
Consumption Function is the curve representing relationship between Consumption spending and Income.
C = a + bY ; where :- C = Consumption , Y = Income , a = Autonomous Consumption i.e consumption at 0 level of income , b = MPC i.e additional consumption consumed from additional income = ΔC / ΔY
b = MPC i.e change in C due to additional change in Y = ΔC / ΔY is the slope of Consumption Function
MPC = ΔC / ΔY .
So, change in consumption i.e ΔC = MPC X ΔY
Answer:
Total cash collection= $530,000
Explanation:
Giving the following information:
<u>Sales:</u>
February $500,000
March $400,000
April $600,000
60% of the credit sales are collected in the month of sale, 30% in the month following sale, and 10% in the second month following the sale.
<u>Cash collection April:</u>
Cash collection credit sales from April= (600,000*0.6)= 360,000
Cash collection credit sales from March= (400,000*0.3)= 120,000
Cash collection credit sales from February= (500,000*0.1)= 50,000
Total cash collection= $530,000
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:
