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sweet-ann [11.9K]
3 years ago
12

A real estate agent is working for a developer who claims that the average commute time to downtown is 20 minutes with a standar

d deviation of 7 minutes. Stephon is an independent real estate agent and wants to check the times for his client. He took a random sample of 15 commute times and found an average of 26 minutes. He did hypothesis testing using a significance level of 5%. Which conclusion could he make?
Mathematics
2 answers:
vova2212 [387]3 years ago
8 0

the answer is C. the z- statistic is 3.32, so the null hypothesis should be rejected.

torisob [31]3 years ago
4 0

To calculate the z-statistic, we must first calculate the standard error.

Standard error is standard deviation divided by the square root of the population. In this case, it is equal to 1.81.

The z-score is defined the distance from the sample to the population mean in units of standard error.

z = (26 – 20)/1.81 = 3.31

at this z-score = 0.0005 which is less than 5%

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Write an equation of the line passing through point p that is parallel to the given line.
Thepotemich [5.8K]

Answer:

Step-by-step explanation:

y=-3x+13

y = mx + b, where m is the slope and b is the y-intercept.

A line parallel to this line will have the same slope, -3.  We can start by writing:

y = -3x + b

No matter what is chosen for the value of b, this line will be parallel.  We do want the line to go through point (6,10), however.  The way that can be done is to find a value of b that would shift the line to go through (6,10).

Find b by entering the point (6,10) into the equation, and then solve for b:

y = -3x + b

10 = -3(6) + b

10 = -18 + b

b = 28

The line becomes y = 3x + 28

See the attachment.

8 0
3 years ago
Let X denote the time from the present until the stock market hits 25,000. If X ≤ 1, you win $10, 000X. If X &gt; 1, you win not
const2013 [10]

Answer: $6321

Step-by-step explanation:

Expected value is given as exactly what you might think it means intuitively, the return you can expect for some type of action.

The basic expected value formula is the probability of an event multiplied by the amount of times the event happens:(P(x) * n).

he formula for the Expected Value for a binomial random variable is:

P(x) * X.

X is the number of trials and P(x) is the probability of success.

The formula for calculating the Expected Value where there are multiple probabilities is:

E(X) = ∑X * P(X)

The equation is basically the same, but here you are adding the sum of all the gains multiplied by their individual probabilities instead of just one probability.

Calculating the expected value of winning as follows:

Given,

Fx= e^-x, x is greater or equal to 0

Now, P less than or equal to zero =

[-e^-x] ^1

e^-0 - e^-1

= 1 - e^-1

= 0.6321

and P(x>1) = 1-0.6321= 0.3679

Therefore,Let y= amount of winnings.

Based on the above given information,

y= $10000 0

P(y)= 0.6321 0.3679

The expected value of winning:

E(y) = ΣyP(y)

E(y) = 10000 × 0.6321 + 0 × 0.3679

E(y) = $6321

Therefore, the expected value of winning is $6321

5 0
3 years ago
susan mountain elevation is 1530 meters. After 4 hours of climbing down to her elvationis 680 meters. What is susans avarge chan
iVinArrow [24]

Answer:

-850 is the answer

Step-by-step explanation:

8 0
3 years ago
Read 2 more answers
Find -3a2 - b3 + 3c2 - 2b3 if a = 2, b = -1, and c = 3
Studentka2010 [4]
If you would like to solve - 3 * a^2 - b^3 + 3 * c^2 - 2 * b^3, if a = 2, b = -1, c = 3, you can calculate this using the following steps:

a = 2, b = -1, c = 3
- 3 * a^2 - b^3 + 3 * c^2 - 2 * b^3 = - 3 * 2^2 - (-1)^3 + 3 * 3^2 - 2 * (-1)^3 = - 3 * 4 - (-1) + 3 * 9 - 2 * (-1) = - 12 + 1 + 27 + 2 = 18

The correct result would be 18.

6 0
3 years ago
Read 2 more answers
If s is an increasing function, and t is a decreasing function, find Cs(X),t(Y ) in terms of CX,Y .
Sedbober [7]

Answer:

C(X,Y)(a,b)=1−C(s(X),t(Y))(a,1−b).

Step-by-step explanation:

Let's introduce the cumulative distribution of (X,Y), X and Y :

F(X,Y)(x,y)=P(X≤x,Y≤y)

  • FX(x)=P(X≤x)
  • FY(y)=P(Y≤y).

Likewise for (s(X),t(Y)), s(X) and t(Y) :

F(s(X),t(Y))(u,v)=P(s(X)≤u

  • t(Y)≤v)
  • Fs(X)(u)=P(s(X)≤u)
  • Ft(Y)(v)=P(t(Y)≤v).

Now, First establish the relationship between F(X,Y) and F(s(X),t(Y)) :

F(X,Y)(x,y)=P(X≤x,Y≤y)=P(s(X)≤s(x),t(Y)≥t(y))

The last step is obtained by applying the functions s and t since s preserves order and t reverses it.

This can be further transformed into

F(X,Y)(x,y)=1−P(s(X)≤s(x),t(Y)≤t(y))=1−F(s(X),t(Y))(s(x),t(y))

Since our random variables are continuous, we assume that the difference between t(Y)≤t(y) and t(Y)<t(y)) is just a set of zero measure.

Now, to transform this into a statement about copulas, note that

C(X,Y)(a,b)=F(X,Y)(F−1X(a), F−1Y(b))

Thus, plugging x=F−1X(a) and y=F−1Y(b) into our previous formula,

we get

F(X,Y)(F−1X(a),F−1Y(b))=1−F(s(X),t(Y))(s(F−1X(a)),t(F−1Y(b)))

The left hand side is the copula C(X,Y), the right hand side still needs some work.

Note that

Fs(X)(s(F−1X(a)))=P(s(X)≤s(F−1X(a)))=P(X≤F−1X(a))=FX(F−1X(a))=a

and likewise

Ft(Y)(s(F−1Y(b)))=P(t(Y)≤t(F−1Y(b)))=P(Y≥F−1Y(b))=1−FY(F−1Y(b))=1−b

Combining all results we obtain for the relationship between the copulas

C(X,Y)(a,b)=1−C(s(X),t(Y))(a,1−b).

7 0
3 years ago
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