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Nataly_w [17]
3 years ago
7

At a specific point on a highway, vehicles arrive according to a Poisson process. Vehicles are counted in 12 second intervals, a

nd vehicle counts are taken in 120 of these time intervals. No cars arrive in 15 of these 120 intervals. a. Approximate the number of these intervals in which exactly one car arrives. (1 point) b. Estimate the percentage of time headways that will be 14 seconds or greater. (1 point) Hint: use t=14 seconds and x=0
Mathematics
1 answer:
morpeh [17]3 years ago
7 0

Answer: a) 4.6798, and b) 19.8%.

Step-by-step explanation:

Since we have given that

P(n) = \dfrac{15}{120}=0.125

As we know the poisson process, we get that

P(n)=\dfrac{(\lambda t)^n\times e^{-\lambda t}}{n!}\\\\P(n=0)=0.125=\dfrac{(\lambda \times 14)^0\times e^{-14\lambda}}{0!}\\\\0.125=e^{-14\lambda}\\\\\ln 0.125=-14\lambda\\\\-2.079=-14\lambda\\\\\lambda=\dfrac{2.079}{14}\\\\0.1485=\lambda

So, for exactly one car would be

P(n=1) is given by

=\dfrac{(0.1485\times 14)^1\times e^{-0.1485\times 14}}{1!}\\\\=0.2599

Hence, our required probability is 0.2599.

a. Approximate the number of these intervals in which exactly one car arrives

Number of these intervals in which exactly one car arrives is given by

0.2599\times 18=4.6798

We will find the traffic flow q such that

P(0)=e^{\frac{-qt}{3600}}\\\\0.125=e^{\frac{-18q}{3600}}\\\\0.125=e^{-0.005q}\\\\\ln 0.125=-0.005q\\\\-2.079=-0.005q\\\\q=\dfrac{-2.079}{-0.005}=415.88\ veh/hr

b. Estimate the percentage of time headways that will be 14 seconds or greater.

so, it becomes,

P(h\geq 14)=e^{\frac{-qt}{3600}}\\\\P(h\geq 14)=e^{\frac{-415.88\times 14}{3600}}\\\\P(h\geq 14)=0.198\\\\P(h\geq 14)=19.8\%

Hence, a) 4.6798, and b) 19.8%.

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<u><em>Step-by-step explanation:</em></u>

<u>Explanation</u>:-

Given data a random sample of 20 turkeys sold at the chain's stores in Detroit yielded a sample mean of 17.53 pounds, with a sample standard deviation of 3.2 pounds

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<em>mean of the first sample 'x₁⁻'= 17.53 pounds</em>

<em>standard deviation of first sample  S₁ = 3.2 pounds</em>

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<em>The second sample size  n₂ = 24</em>

<em>mean of the second sample  "x₂⁻"= 14.89 pounds</em>

<em>standard deviation of second sample  S₂ =  2.7 poun</em>ds

<u><em>Null hypothesis</em></u><u>:-</u><u><em>H₀</em></u><em>: The Population Variance are approximately same</em>

<u><em>Alternatively hypothesis</em></u><em>: H₁:The Population Variance are approximately same</em>

<em>Level of significance ∝ =0.05</em>

<em>Degrees of freedom ν = n₁ +n₂ -2 =20+24-2 = 42</em>

<em>Test statistic :-</em>

<em>    </em>t = \frac{x^{-} _{1} -  x_{2} }{\sqrt{S^2(\frac{1}{n_{1} } }+\frac{1}{n_{2} }  }

<em>    where         </em>S^{2}   = \frac{n_{1} S_{1} ^{2}+n_{2}S_{2} ^{2}   }{n_{1} +n_{2} -2}

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<em>              substitute values and we get  S² =  40.988</em>

<em>     </em>t= \frac{17.53-14.89 }{\sqrt{40.988(\frac{1}{20} }+\frac{1}{24}  )}<em></em>

<em>  </em>   t =  1.3622

  Calculated value t = 1.3622

Tabulated value 't' =  2.081

Calculated value t = 1.3622 < 2.081 at 0.05 level of significance with 42 degrees of freedom

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<em>The null hypothesis is accepted </em>

<em>Assume the population variances are approximately the same.</em>

<em>      </em>

<em>                        </em>

<em>                    </em>

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