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kkurt [141]
3 years ago
9

During summer weekdays, boats arrive at the inlet drawbridge according to Poisson distribution at a rate of 3 per hour. In a 2-h

our period, what is the probability that no boats arrive
Mathematics
1 answer:
mrs_skeptik [129]3 years ago
6 0

Answer:

The probability that no boats arrive is 2.48\times 10^{-3}.

Step-by-step explanation:

Poisson distribution:

Poisson distribution is a statistical distribution that helps to find out the probability of a certain is likely occur a specified period of time.

P(X=x)=\frac{e^{-\lambda t}(\lambda t)^x}{x!}

\lambda = rate.

Given that, Poisson distribution at a rate of 3 per hour.

\lambda = 3

t=2

x=0

The probability that no boats arrive is

P(X=0)=\frac{e^{-2\times 3}(2\times 3)^0}{0!}

                =2.48\times 10^{-3}

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Assuming that the triangle is a right triangle, we can reverse engineer the Pythagorean theorem (a^2+b^2=c^2).

60^2 + x^2 = 61^2

3600 + x^2 = 3721

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x^2 = 121

x = sqrt121

x = 11

8 0
3 years ago
Alex leaves school to go home. He walks 11 meters North and then 10 meters West. How far is Alex from the school?
yuradex [85]

Answer:

~15 meters away

Step-by-step explanation:

c^2 = a^2+b^2

c^2 = 10^2+11^2

c^2 = 100+121

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c = \sqrt{221}

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2 years ago
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Step-by-step explanation:

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Each morning, Hungry Harry eats some eggs. On any given morning, the number of eggs he eats is equally likely to be 1, 2, 3, 4,
mamaluj [8]

Answer:

Mean = 35

Variance = 291.7

Step-by-step explanation:

Data provided in the question:

X : 1, 2, 3, 4, 5, 6

All the data are independent

Thus,

The mean for this case will be given as:

Mean, E[X] = \frac{\textup{Sum of all the observations}}{\textup{Total number of observations}}

or

 E[X] = \frac{\textup{1+2+3+4+5+6}}{\textup{6}}

or

E[X] = 3.5

For 10 days, Mean = 3.5 × 10 = 35

And,

variance = E[X²] - ( E[X] )²

Now, for this case of independent value,

E[X²] = \frac{1^2+2^2+3^2+4^2+5^2+6^2}{\textup{6}}

or

E[X²] = \frac{1+4+9+16+25+36}{\textup{6}}

or

E[X²] = \frac{91}{\textup{6}}

or

E[X²] = 15.167

Therefore,

variance = E[X²] - ( E[X] )²

or

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or

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For 10 days = Variance × Days²

= 2.917 × 10²

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3 years ago
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