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ss7ja [257]
2 years ago
6

Blanche bought a 5-year cd for $7100 with an apr of 2.8%, compounded quarterly, but she wants to take all her money out 9 months

early. the early redemption fee for the cd is 3 months' interest on the original principal. help blanche determine how much money she will end up earning in interest on the cd. (5 points: part i – 1 point; part ii – 1 point; part iii – 1 point; part iv – 1 point; part v – 1 point)
Mathematics
1 answer:
katrin2010 [14]2 years ago
4 0
The formula for getting the accumulated amount(compounded) is;
A =P(1+r%)∧n
Where A = Acumulated amount 
            P = principle (deposit)
            r = interest rate and
            n = period
Since the interst is compounded quartly, 
period = (5×4)-3 = 17

A = 7100(1+2.8/100)∧17
   = 7100×1.028∧17
   = 11,353.80

The money she will end up earning in interest on the cd = $11,353.80
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a) For this case we can find the cumulative distribution function first:

F(k) = P(Y \leq k) = \sum_{k'=1}^k P(Y =k')= \sum_{k'=1}^k p(1-p)^{k'-1}= 1-(1-p)^k

So then by the complement rule we have this:

P(Y>a) = 1-F(a)= 1- [1-(1-p)^a]= 1-1 +(1-p)^a = (1-p)^a = q^a

b) P(Y>a)= q^a

P(Y>b) = q^b

So then we have this using independence:

P(Y> a+b) = q^{a+b}

We want to find the following probability:

P(Y> a+b |Y>a)

Using the definition of conditional probability we got:

P(Y> a+b |Y>a)= \frac{P(Y> a+b \cap Y>a)}{P(Y>a)} = \frac{P(Y>a+b)}{P(Y>a)} = \frac{q^{a+b}}{q^a} = q^b = P(Y>b)

And we see that if a = 2 and b=5 we have:

P(Y> 2+5 | Y>2) = P(Y>5)

c) For this case we use independent identical and with the same distribution experiments.

And the result for part b makes sense since we are interest in find the probability that the random variable of interest would be higher than an specified value given another condition with a value lower or equal.

Step-by-step explanation:

Previous concepts

The geometric distribution represents "the number of failures before you get a success in a series of Bernoulli trials. This discrete probability distribution is represented by the probability density function:"

P(X=x)=(1-p)^{x-1} p

If we define the random of variable Y we know that:

Y\sim Geo (1-p)

Part a

For this case we can find the cumulative distribution function first:

F(k) = P(Y \leq k) = \sum_{k'=1}^k P(Y =k')= \sum_{k'=1}^k p(1-p)^{k'-1}= 1-(1-p)^k

So then by the complement rule we have this:

P(Y>a) = 1-F(a)= 1- [1-(1-p)^a]= 1-1 +(1-p)^a = (1-p)^a = q^a

Part b

For this case we can use the result from part a to conclude that:

P(Y>a)= q^a

P(Y>b) = q^b

So then we have this assuming independence:

P(Y> a+b) = q^{a+b}

We want to find the following probability:

P(Y> a+b |Y>a)

Using the definition of conditional probability we got:

P(Y> a+b |Y>a)= \frac{P(Y> a+b \cap Y>a)}{P(Y>a)} = \frac{P(Y>a+b)}{P(Y>a)} = \frac{q^{a+b}}{q^a} = q^b = P(Y>b)

And we see that if a = 2 and b=5 we have:

P(Y> 2+5 | Y>2) = P(Y>5)

Part c

For this case we use independent identical and with the same distribution experiments.

And the result for part b makes sense since we are interest in find the probability that the random variable of interest would be higher than an specified value given another condition with a value lower or equal.

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