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icang [17]
3 years ago
5

One shape is approaching a poor from the east traveling west at 15 mph and its presently 3 miles east east of the port I second

ship is already left the poor traveling to the north at 10 mph and is presently 4 miles north of the port at this instant what is the rate of change of distance between the two ships are they going to close your more for their apart
Mathematics
1 answer:
valentinak56 [21]3 years ago
4 0

Answer:

DL/dt = 17 mph

Step-by-step explanation:

The ships and the port shape a right triangle

Ship  going west ( x-direction)   is traveling at 15 mph

Ship going north  (y-direction) is traveling at 10 mph

The distance L between ships is:

L²  = x² + y²

Tacking derivatives on both sides of the equation with respect to time

we get

2*L*DL/dt = 2*x*Dx/dt  + 2*y*Dy/dt    (1)

In that equation we know:

Dx/dt  = 15 mph

Dy/dt  = 10 mph

At the moment  ship traveling from the east is at 3 miles from the port

then x = 3 m  and the other ship is at 4 miles north

then by Pythagoras theorem

L = √ 3² + 4²    L = 5

By substitution in equation 1

2*5*DL/dt  = 2*3*15 + 2*4*10

10* DL/dt  =  90  +  80

DL/dt = 170 / 10

DL/dt = 17 mph

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So if she has to go more than 2 miles we will put 2 in for X

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.55×2= 1.10+1.75= 2.85
2.85 is greater than 10 is false so now we know she has to go more than 2 miles.

Let's guess and check. Now let's say 15 miles
.55×15= 8.25+1.75= 10
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x is greater than or equal to 15

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Read 2 more answers
An honest die is rolled. If the roll comes out even (2, 4, or 6), you will win $1; if the roll comes out odd (1,3, or 5), you wi
jenyasd209 [6]

Answer:

(a) 50%

(b) 47.5%

(c) 2.5%

Step-by-step explanation:

According to the honest coin principle, if the random variable <em>X</em> denotes the number of heads in <em>n</em> tosses of an honest coin (<em>n</em> ≥ 30), then <em>X</em> has an approximately normal distribution with mean, \mu=\frac{n}{2} and standard deviation, \sigma=\frac{\sqrt{n}}{2}.

Here the number of tosses is, <em>n</em> = 2500.

Since <em>n</em> is too large, i.e. <em>n</em> = 2500 > 30, the random variable <em>X</em> follows a normal distribution.

The mean and standard deviation are:

\mu=\frac{n}{2}=\frac{2500}{2}=1250\\\\\sigma=\frac{\sqrt{n}}{2}=\frac{\sqrt{2500}}{2}=25

(a)

To not lose any money the even rolls has to be 1250 or more.

Since, <em>μ</em> = 1250 it implies that the 50th percentile is also 1250.

Thus, the probability that by the end of the evening you will not have lost any money is 50%.

(b)

If the number of "even rolls" is 1250, it implies that the percentile of 1250 is 50th.

Then for number of "even rolls" as 1300,

1300 = 1250 + 2 × 25

        = μ + 2σ

Then P (μ + 2σ) for a normally distributed data is 0.975.

⇒ 1300 is at the 97.5th percentile.

Then the area between 1250 and 1300 is:

Area = 97.5% - 50%

        = 47.5%

Thus, the probability that the number of "even rolls" will fall between 1250 and 1300 is 47.5%.

(c)

To win $100 or more the number of even rolls has to at least 1300.

From part (b) we now 1300 is the 97.5th percentile.

Then the probability that you will win $100 or more is:

P (Win $100 or more) = 100% - 97.5%

                                   = 2.5%.

Thus, the probability that you will win $100 or more is 2.5%.

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