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AURORKA [14]
3 years ago
5

Customers arrive randomly and independently at a service window, and the time between arrivals has an exponential distribution w

ith a mean of 12 minutes. Let X equal the number of arrivals per hour. What is P(X=10)?
Mathematics
1 answer:
STALIN [3.7K]3 years ago
3 0

Answer:

0.018133

Step-by-step explanation:

Given that customers  arrive randomly and independently at a service window, and the time between arrivals has an exponential distribution with a mean of 12 minutes.

Let X equal the number of arrivals per hour.

X is having average as  reciprocal of 12 minutes

i.e. in one hour on an average expected customers to arrive is 60/12 =5

X being reciprocal of exponential is Poisson with parameter = 5

Probability that 10 customers arrive in one hour

=P(X=10)

=0.018133

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erica [24]

Answer:

The explanation is given below.

Step-by-step explanation:

Given:

Two events take place.

Let event A be flipping a coin

Let event B be rolling a 6-sided die.

Now, a coin has two faces; one is head and the other is tail.

So, the possible outcomes of event A are: {H, T}

H → Head, T → Tail.

Now, a six sided die has six faces each marked with a number. The numbers marked ranges from 1 to 6.

So, the possible outcomes of event B are {1, 2, 3, 4, 5, 6}

Now, each element of set A should match with all the elements of set B.

Now, tabular form should have a row of outcomes of B and a coum of outcomes of event A. Thus,

Outcomes          1          2       3        4         5          6  

   H                 H1         H2     H3     H4       H5      H6

   T                 T1         T2     T3        T4      T5         T6

Therefore, the organised list has the following outcomes:

H1                 T1        

H2                T2

H3                T3

H4                T4

H5                T5

H6                T6

Finally, the correct tree diagram is attached below.

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A university found that 20% of its students withdraw without completing the introductory statistics course. Assume that 20 stude
bulgar [2K]

Answer:

a) 20.61%

b) 21.82%

c) 42.36%

d) 4 withdrawals

Step-by-step explanation:

This situation can be modeled with a binomial distribution, where p = probability of “success” (completing the course) equals 80%  = 0.8 and the probability of “failure” (withdrawing) equals 0.2.

So, the probability of exactly k withdrawals in 20 cases is given by

\large P(20;k)=\binom{20}{k}(0.2)^k(0.8)^{20-k}

a)

We are looking for

P(0;20)+P(0;1)+P(0;2) =  

\large \binom{20}{0}(0.2)^0(0.8)^{20}+\binom{20}{1}(0.2)^1(0.8)^{19}+\binom{20}{2}(0.2)^2(0.8)^{18}=

0.0115292150460685 + 0.0576460752303424 + 0.136909428672063 = 0.206084718948474≅ 0.2061 or 20.61%

b)

Here we want P(20;4)

\large P(20;4)=\binom{20}{4}(0.2)^4(0.8)^{16}=0.218199402\approx 0.2182=21.82\%

c)

Here we need

\large \sum_{k=4}^{20}P(20;k)=1-\sum_{k=1}^{3}P(20;k)

But we already have P(0;20)+P(0;1)+P(0;2) =0.2061 and

\large \sum_{k=1}^{3}P(20;k)=0.2061+P(20;3)=0.2061+0.205364 \approx 0.4236=42.36\%

d)

For a binomial distribution the <em>expectance </em>of “succeses” in n trials is np where p is the probability of “succes”, and the expectance of “failures” is nq, so the expectance for withdrawals in 20 students is 20*0.2 = <em>4 withdrawals.</em>

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Answer

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Step-by-step explanation:

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