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dlinn [17]
3 years ago
14

A parking lot has two entrances. Cars arrive at entrance I according to a Poisson distribution at an average of 3 per hour and a

t entrance II according to a Poisson distribution at an average of 2 per hour. What is the probability that a total of 3 cars will arrive at the parking lot in a given hour? What is the probability that less than 3 cars will arrive at the parking lot in a given hour? (Assume that the numbers of cars arriving at the two entrances are independent. (Note: The probability mass function of Poisson distribution is p(x) = (e^-λ * λ^x)/(x!) for x = 0,1,2, ..., , where λ is the parameter which indicates the average number of events in the given time interval.)
Mathematics
2 answers:
alina1380 [7]3 years ago
7 0

Answer:

Step-by-step explanation:

Given that a parking lot has two entrances. Cars arrive at entrance I according to a Poisson distribution at an average of 3 per hour and at entrance II according to a Poisson distribution at an average of 2 per hour.

Assuming the number of cars arriving at the two parking lots are independent we have total number of cars arriving X is Poisson with parameter 3+2 = 5

X is Poisson with mean = 5

the probability that a total of 3 cars will arrive at the parking lot in a given hour

= P(X=3) = 0.1404

b)  the probability that less than 3 cars will arrive at the parking lot in a given hour

= P(X<3)

= P(0)+P(1)+P(2)

= 0.1247

lys-0071 [83]3 years ago
6 0

Answer:

(a) the probability that a total of 3 cars will arrive at the parking lot in a given hour is 0.1404.

(b) The probability that less than 3 cars will arrive at the parking lot in a given hour is 0.1247.

Step-by-step explanation:

Let <em>X</em> = cars arriving through entrance I and <em>Y</em> = cars arriving through entrance II.

<u>Given:</u>

X\sim Poisson(3)\\Y\sim Poisson (2)

The probability function of a Poisson distribution is:

P(U=u)=\frac{\lambda^{u}e^{-\lambda}}{u!}

It is also provided that the events <em>X</em> and <em>Y</em> are independent.

Let <em>U </em>= <em>X</em> + <em>Y</em>

Then E (U) = E (X) + E(Y) = 3 + 2 = 5.

The random variable <em>U</em><em> </em>also follows a Poisson distribution with parameter <em>λ</em> = 5

(a)

The probability that a total of 3 cars will arrive at the parking lot in a given hour is:

P(U=3)=\frac{5^{3}e^{-5}}{3!}\\=\frac{125\times0.00674}{6} \\=0.1404

Thus, the probability that a total of 3 cars will arrive at the parking lot in a given hour is 0.1404.

(b)

The probability that less than 3 cars will arrive at the parking lot in a given hour is:

P(U

Thus, the probability that less than 3 cars will arrive at the parking lot in a given hour is 0.1247.

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Step-by-step explanation:

For each property, there are only two possible outcomes. Either it is sold, or it is not. The chance of selling any one property is independent of selling another property. So we use the binomial probability distribution to solve this question.

Binomial probability distribution

The binomial probability is the probability of exactly x successes on n repeated trials, and X can only have two outcomes.

P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}

In which C_{n,x} is the number of different combinations of x objects from a set of n elements, given by the following formula.

C_{n,x} = \frac{n!}{x!(n-x)!}

And p is the probability of X happening.

In this problem we have that:

n = 14, p = 0.5

Compute the probability of selling more than 4 properties in one week.

Either you sell 4 or less properties in one week, or you sell more. The sum of the probabilities of these events is decimal 1. So

P(X \leq 4)  + P(X > 4) = 1

We want to find P(X > 4). So

P(X > 4) = 1 - P(X \leq 4)

In which

P(X \leq 4) = P(X = 0) + P(X = 1) + P(X = 2) + P(X = 3) + P(X = 4)

So

P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}

P(X = 0) = C_{14,0}.(0.5)^{0}.(0.5)^{14} = 0.000061

P(X = 1) = C_{14,1}.(0.5)^{1}.(0.5)^{13} = 0.000854

P(X = 2) = C_{14,2}.(0.5)^{2}.(0.5)^{12} = 0.0056

P(X = 3) = C_{14,3}.(0.5)^{3}.(0.5)^{11} = 0.0222

P(X = 4) = C_{14,4}.(0.5)^{4}.(0.5)^{10} = 0.0611

So

P(X \leq 4) = P(X = 0) + P(X = 1) + P(X = 2) + P(X = 3) + P(X = 4) = 0.000061 + 0.000854 + 0.0056 + 0.0222 + 0.0611 = 0.0898

Finally

P(X > 4) = 1 - P(X \leq 4) = 1 - 0.0898 = 0.9102

91.02% probability of selling more than 4 properties in one week.

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$5.481 * 36 (months) = $197.146

$18,795.02 = $1,605 + $197.146

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