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madreJ [45]
2 years ago
8

You have 250,000 In an IRA at the time you retire.You have the option of investing this money in two funds.Fund A pays 1.2% annu

ally and Fund B pays 6.2% annually.How should you divide your money between Fund A and Fund B to produce and annual interest income of $8,000?
Mathematics
1 answer:
krok68 [10]2 years ago
8 0

Let x be the amount of money, you fund in Fund A and y be the amount of mone yyou fund in Fund B.

1. You have 250,000 In an IRA at the time you retire and want to invest this money into Funds A and B, then

x+y=250,000.

2. Fund A pays 1.2% (as a decimal 1.2% is 0.012) annually, then x\cdot 0.012=0.012x is annual interest income in Fund A.

Fund B pays 6.2% (as a decimal 6.2% is 0.062) annually, then y\cdot 0.062=0.062y is annual interest income in Fund B.

Since Fund A and Fund B produce an annual interest income of $8,000, then

0.012x+0.062y=8,000.

3. Solve the system of equations:

\left\{\begin{array}{l}x+y=250,000\\0.012x+0.062y=8,000.\end{array}\right.

Express x from first equation x=250,000-y and substitute it into the second equation

0.012(250,000-y)+0.062y=8,000.

Multiply this equation by 1000:

12(250,000-y)+62y=8000,000,\\ \\3000,000-12y+62y=8000,000,\\ \\62y-12y=8000,000-3000,000,\\ \\50y=5000,000,\\ \\y=100,000

Then

x=250,000-100,000=150,000.

Answer: you have to fund $150,000 in Fund A and $100,000 in Fund B.


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A linear regression model is fitted to the data x y 37.0 65.0 36.4 67.2 35.8 70.3 34.3 71.9 33.7 73.8 32.1 75.7 31.5 77.9 with x
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Answer:

b0= 144.59

b= -2.12

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99%CI E(Y/X=35): [68.78; 71.99]

Step-by-step explanation:

Hello!

I've arranged the given data:

X: 37.0, 36.4, 35.8, 34.3, 33.7, 32.1, 31.5

Y: 65.0, 67.2, 70.3, 71.9, 73.8, 75.7, 77.9

The equation of the linear regression model is:

Yi= β₀ + βXi + εi

Where

Yi is the dependent variable

Xi is the independent variable

εi represents the errors or residues

β₀ is the intercept of the line

β is the slope

The conditions to make a linear regression analysis are:

For each given value of X, there is a population of Y~N(μy;σy²)

Each value of Y is independent of the others.

The population variances of each population of Y are equal.

From these conditions the following characteristic is deduced:

εi~N(0;σ²)

The parameters of the regression are:

β₀, β, and σ²

If the conditions are met then you can estimate the regression line:

Yi= bo * bXi + ei.

And the point estimation of the parameters can be calculated using the formulas:

β₀ ⇒ b0= (∑y/n)-b(∑x/n)

β ⇒ b= [∑xy- ((∑x)(∑y))/n]/(∑x²-((∑x)²/n))

σ²⇒ Se²= 1/(n-2)*[∑y²-(∑y)²/n - b²(∑x²-(∑x)²/n)]

n= 7

∑y= 501.80

∑y²= 36097.88

∑x= 240.80

∑x²= 8310.44

∑xy= 17204.87

b0= 144.59

b= -2.12

Se²= 1.02

The estimated regression line is:

Yi= 144.59 -2.12Xi

You need to calculate a 99%CI E(Y/X=35), the formula is:

(b0 + bX0) ± t_{n-2;1-\alpha /2}*\sqrt{S_e^2(\frac{1}{n}+\frac{(X_0-X[bar])^2}{sumX^2-(\frac{(sumX)^2}{n} )} )}

(144.59 + (-2.12*35)) ± 4.032*\sqrt{1.02(\frac{1}{7}+\frac{(35-34.4)^2}{8310.44-(\frac{(240.80)^2}{7} )} )}

[68.78; 71.99]

With a 99% confidence level youd expect that the interval [68.78; 71.99] contains the true value of the average of Y when X= 35.

I hope it helps!

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