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IgorLugansk [536]
3 years ago
7

A financial company advertises on television that they will pay you $55,000 now in exchange for annual payments of $8,500 that y

ou
are expected to receive for a legal settlement over the next 10 years. You estimate the time
value of money at 7 percent
(a) Calculate the present value of the annual payments. Use Exhibit 1-D. (Round time value factor to 3 decimal places and final
answer to the nearest whole number.)
Present value
(b) Would you accept this offer?
No
Yes
Pro
of 10
Mout

Mathematics
1 answer:
Lena [83]3 years ago
3 0

dunno sorry

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klemol [59]

Your question is calling the figure ABCD, but the image is showing PQRS


Using the letters that you wrote:

Because the figure was only rotated and not scaled , the sides with the same letters would still be the same

So AB would be the same as A'B' ( Length of AB = Length of A′B)

and

BC = B'C'

CD = C'D'

AD = A'D'


Or by the picture:

PQ = P'Q'

QR = Q'R'

RS = R'S'

PS = P'S'





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Professor wonders whether a student's homework average (X) could be used to predict their final grade in the course (Y) . She ca
Anna11 [10]

Answer:

The dependent variable is the final grade in the course and is the vriable of interest on this case.

H0: \beta_1 = 0

H1: \beta_1 \neq 0

And if we reject the null hypothesis we can conclude that we have a significant relationship between the two variables analyzed.

Step-by-step explanation:

On this case w ehave the following linear model:

Y= 21.839 +0.724 X

Where Y represent the final grade in the course and X the student's homework average. For this linear model the slope is given by \beta_1 = 0.724 and the intercept is \beta_0 = 21.839

Which is the dependent variable, and why?

The dependent variable is the final grade in the course and is the vriable of interest on this case.

Based on the material taught in this course, which of the following is the most appropriate alternative hypothesis to use for resolving this question?

Since we conduct a regression the hypothesis of interest are:

H0: \beta_1 = 0

H1: \beta_1 \neq 0

And if we reject the null hypothesis we can conclude that we have a significant relationship between the two variables analyzed.

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Step-by-step explanation:

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