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2 years ago

To have $25,000 to spend on a new car in five years, how much money should Jill invest today at 8% compounded monthly?

Mathematics

2 answers:

finlep [7]2 years ago

8 0

Answer:

The answer is C. $16,780

Step-by-step explanation:

$PV = 25,000(1+\frac{0.08}{12} )x^{-12(5)} = 16,780$

Mariulka [41]2 years ago

7 0

The answer is B
Because if you use your calculation right you would end up with 16,463

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The perimeter of the norwegian flag is 190 inches. What are the dimensions of the flag?

mario62 [17]

The dimensions are 40 inches by 55 inches.

Explanation:
We know that perimeter is the sum of all of the sides. Since this is rectangular, opposite sides are equal. This gives us
y+11/8y+y+11/8y=190.

Combining like terms, we have
2y+22/8y=190.

Writing 22/8 as a mixed number, we have
2y+2 3/4y=190
4 3/4y=190.

Divide both sides by 4 3/4:
(4 3/4y)÷(4 3/4)=190÷(4 3/4)
y=190÷(4 3/4).

Convert the mixed number to an improper fraction:
y=190÷(19/4).

To divide fractions, flip the second one and multiply:
y=190*(4/19)=760/19=40.

Since y=40, 11/8y=11/8(40)=440/8=55.

8 0

2 years ago

Which of the following shows the extraneous solution to the logarithmic equation? log Subscript 4 Baseline (x) + log Subscript 4

vekshin1

Given:

The given equation is $\log _{4}(x)+\log _{4}(x-3)=\log _{4}(-7 x+21)$

We need to determine the extraneous solution of the equation.

Solving the equation:

To determine the extraneous solution, we shall first solve the given equation.

Applying the log rule $\log _{c}(a)+\log _{c}(b)=\log _{c}(a b)$ , we get;

$\log _{4}(x(x-3))=\log _{4}(-7 x+21)$

Again applying the log rule, if $\log _{b}(f(x))=\log _{b}(g(x))$ then $f(x)=g(x)$

Thus, we have;

$x(x-3)=-7 x+21$

Simplifying the equation, we get;

$x^2-3x=-7 x+21$

$x^2+4x=21$

$x^2+4x-21=0$

Factoring the equation, we get;

$(x-3)(x+7)=0$

Thus, the solutions are $x=3, x=-7$

Extraneous solutions:

The extraneous solutions are the solutions that does not work in the original equation.

Now, to determine the extraneous solution, let us substitute x = 3 and x = -7 in the original equation.

Thus, we get;

$\log _{4}(3)+\log _{4}(3-3)=\log _{4}(-7 \cdot 3+21)$

$\log _{4}(3)+\log _{4}(0)=\log _{4}(0)$

Since, we know that $\log _{a}(0)$ is undefined.

Thus, we get;

Undefined = Undefined

This is false.

Thus, the solution x = 3 does not work in the original equation.

Hence, x = 3 is an extraneous solution.

Similarly, substituting x = -7, in the original equation. Thus, we get;

$\log _{4}(-7)+\log _{4}(-7-3)=\log _{4}(-7(-7)+21)$

$\log _{4}(-7)+\log _{4}(-10)=\log _{4}(49+21)$

$\log _{4}(-7)+\log _{4}(-10)=\log _{4}(70)$

Simplifying, we get;

Undefined = $\log _{4}(70)$

Undefined = 3.06

This is false.

Thus, the solution x = -7 does not work in the original solution.

Hence, x = -7 is an extraneous solution.

Therefore, the extraneous solutions are x = 3 and x = -7

7 0

2 years ago

Read 2 more answers

A member of a student team playing an interactive marketing game received the fol- lowing computer output when studying the rela

nirvana33 [79]

Answer:

$p_v = 2*P(t_{n-2} > |t_{calc}|)= 0.91$

So on this case for the significance level assumed $\alpha=0.05$ we see that $p_v >\alpha$ so then we can conclude that the result is NOT significant. And we don't have enough evidence to reject the null hypothesis.

So on this case is not appropiate say that :"the more we spend on advertising this product, the fewer units we sell" since the slope for this case is not significant.

Step-by-step explanation:

Let's suppose that we have the following linear model:

$y= \beta_o +\beta_1 X$

Where Y is the dependent variable and X the independent variable. $\beta_0$ represent the intercept and $\beta_1$ the slope.

In order to estimate the coefficients $\beta_0 ,\beta_1$ we can use least squares procedure.

If we are interested in analyze if we have a significant relationship between the dependent and the independent variable we can use the following system of hypothesis:

Null Hypothesis: $\beta_1 = 0$

Alternative hypothesis: $\beta_1 \neq 0$

Or in other words we want to check is our slope is significant (X have an effect in the Y variable )

In order to conduct this test we are assuming the following conditions:

a) We have linear relationship between Y and X

b) We have the same probability distribution for the variable Y with the same deviation for each value of the independent variable

c) We assume that the Y values are independent and the distribution of Y is normal

The significance level assumed on this case is $\alpha=0.05$

The standard error for the slope is given by this formula:

$SE_{\beta_1}=\frac{\sqrt{\frac{\sum (y_i -\hat y_i)^2}{n-2}}}{\sqrt{\sum (X_i -\bar X)^2}}$

Th degrees of freedom for a linear regression is given by $df=n-2$ since we need to estimate the value for the slope and the intercept.

In order to test the hypothesis the statistic is given by:

$t=\frac{\hat \beta_1}{SE_{\beta_1}}$

The p value on this case would be given by:

$p_v = 2*P(t_{n-2} > |t_{calc}|)= 0.91$

So on this case is not appropiate say that :"the more we spend on advertising this product, the fewer units we sell" since the slope for this case is not significant.

3 0

2 years ago

House price y is estimated as a function of the square footage of a house x and a dummy variable d that equals 1 if the house ha

tresset_1 [31]

Answer:

a-1. The predicted price of a house with ocean views and square footage of 2,000 is $411,500.00.

a-2. The predicted price of a house with ocean views and square footage of 3,000 is $531,500.00.

b-1. The predicted price (in $1,000s) of a house without ocean views and square footage of 2,000 is $358,900.

b-2. The predicted price of a house without ocean views and square footage of 3,000 is $478,900.00.

c. The correct option is An ocean view increases the value of a house by approximately $52,600.

Step-by-step explanation:

Given:

yˆ = 118.90 + 0.12x + 52.60d ………………. (1)

a-1. Compute the predicted price (in $1,000s) of a house with ocean views and square footage of 2,000. (Round intermediate calculations to at least 4 decimal places. Round your answer to 2 decimal places.)

This implies that we have:

x = 2,000

d = 1

Substituting the values into equation (1), we have:

yˆ = 118.90 + (0.12 * 2000) + (52.60 * 1) = 411.50

Since the predicted price is in $1,000s, we have:

yˆ = 411.50 * $1000

yˆ = $411,500.00

Therefore, the predicted price of a house with ocean views and square footage of 2,000 is $411,500.00.

a-2. Compute the predicted price (in $1,000s) of a house with ocean views and square footage of 3,000. (Round intermediate calculations to at least 4 decimal places. Round your answer to 2 decimal places.)

This implies that we have:

x = 3,000

d = 1

Substituting the values into equation (1), we have:

yˆ = 118.90 + (0.12 * 3,000) + (52.60 * 1) = 531.50

Since the predicted price is in $1,000s, we have:

yˆ = 531.50 * $1000

yˆ = $531,500.00

Therefore, the predicted price of a house with ocean views and square footage of 3,000 is $531,500.00.

b-1. Compute the predicted price (in $1,000s) of a house without ocean views and square footage of 2,000. (Round intermediate calculations to at least 4 decimal places. Round your answer to 2 decimal places.)

This implies that we have:

x = 2,000

d = 0

Substituting the values into equation (1), we have:

yˆ = 118.90 + (0.12 * 2000) + (52.60 * 0) = 358.90

Since the predicted price is in $1,000s, we have:

yˆ = 358.90 * $1000

yˆ = $358,900.00

Therefore, the predicted price of a house without ocean views and square footage of 2,000 is $358,900.00.

b-2. Compute the predicted price (in $1,000s) of a house without ocean views and square footage of 3,000. (Round intermediate calculations to at least 4 decimal places. Round your answer to 2 decimal places.)

This implies that we have:

x = 3,000

d = 0

Substituting the values into equation (1), we have:

yˆ = 118.90 + (0.12 * 3,000) + (52.60 * 0) = 478.90

Since the predicted price is in $1,000s, we have:

yˆ = 478.90 * $1000

yˆ = $478,900.00

Therefore, the predicted price of a house without ocean views and square footage of 3,000 is $478,900.00.

c. Discuss the impact of ocean views on the house price.

Since the coefficient of d in equation (1) is 52.60 and positive, and the predicted price is in $1,000s; the correct option is An ocean view increases the value of a house by approximately $52,600.

3 0

2 years ago

Subject On-Time Assignment Submission On-Time Arrival to Class Physics 89.7% 82.3% Math 88.2% 88.7% Chemistry 89.4% 83.1% Biolog

Alekssandra [29.7K]

Answer:

D. insufficient data

Step-by-step explanation:

We need to know the number of assignments in each class before we can tell the probability of interest.

If we assume the same number of assignments in each class, then 25.1% of on-time assignments were in physics. We note this is not an answer choice, further confirming we have insufficient data.

7 0

2 years ago