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Kay [80]
1 year ago
15

A statistics professor receives an average of five e-mail messages per day from students. assume the number of messages approxim

ates a poisson distribution. what is the probability that on a randomly selected day she will have no messages?
Mathematics
2 answers:
uranmaximum [27]1 year ago
4 0

The probability that on a randomly selected day she will have no messages \boxed{0.00674}.

Further Explanation:

The random variable X follows Poisson distribution.

\boxed{X\~{\text{Poisson}}\left( \lambda  \right)}

Here, \lambda represents the Poisson parameter.

The mean of the Poisson parameter is \lambda.

The variance of the Poisson parameter is \lambda.

The formula for the probability of Poisson distribution can be expressed as follows,

\boxed{P\left( x \right)=\frac{{{e^{- \lambda }}\times {\lambda ^x}}}{{x!}}}

Given:

The number of messages follows Poisson distribution.

The value of \lambda is \lambda = 5.

Explanation:

A statistics professor receives an average of five e-mail messages per day from students.

The mean of the message is 5.

The probability that on a randomly selected day she will have no messages can be obtained as follows,

\begin{aligned}P\left( 0 \right) &= \frac{{{e^{ - 5}} \times {5^0}}}{{0!}}\\&= \frac{{0.00674 \times 1}}{1}\\&= 0.00674\\\end{aligned}

The probability that on a randomly selected day she will have no messages \boxed{0.00674}.

Learn more:

1. Learn more about normal distribution brainly.com/question/12698949

2. Learn more about standard normal distribution brainly.com/question/13006989

3. Learn more about confidence interval of meanhttps://brainly.com/question/12986589

Answer details:

Grade: College

Subject: Statistics

Chapter: Poissondistribution

Keywords: statistics professor, receives, average, five e-mail, message, students, messages per day, Poisson distribution, probability, randomly selected, no message, parameter, probability formula, number of message.

Juliette [100K]1 year ago
3 0
From the problem, we have the following given
u = 5
x = 0

We use the Poisson distribution probability formula:
P = (e^-μ) (μ^x<span>) / x! 
Substituting
P = (e^-5) (5^0) / 0!
P = 0.0067
</span>
The probability is 0.0067 or 0.67%<span />
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r = 0.9825; good correlation.

Step-by-step explanation:

One formula for the correlation coefficient is  

r = \dfrac{n\sum{xy} - \sum{x} \sum{y}}{\sqrt{n\left [\sum{x}^{2}-\left (\sum{x}\right )^{2}\right]\left [\sum{y}^{2}-\left (\sum{y}\right )^{2}\right]}}

The calculation is not difficult, but it is tedious.

1. Calculate the intermediate numbers

We can display them in a table.

      <u> </u><u>x</u>    <u>  y </u>   <u>  xy </u>  <u> x² </u>    <u>   y²   </u>

      -3   -40    120     9     1600

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     <u>  7</u>   <u>137</u>  <u> 959</u>   <u>49</u>    <u>18769 </u>

Σ = 10   181  1451   84   25697

2. Calculate the correlation coefficient

r = \dfrac{n\sum{xy} - \sum{x} \sum{y}}{\sqrt{\left [n\sum{x}^{2}-\left (\sum{x}\right )^{2}\right]\left [n\sum{y}^{2}-\left (\sum{y}\right )^{2}\right]}}\\\\= \dfrac{4\times 1451 - 10\times 181}{\sqrt{[4\times 84 - 10^{2}][4\times25697 - 181^{2}]}}\\\\= \dfrac{5804 - 1810}{\sqrt{[336 - 100][102788 - 32761]}}\\\\= \dfrac{3994}{\sqrt{236\times70027}}\\\\= \dfrac{3994}{\sqrt{16526372}}\\\\= \dfrac{3994}{4065}\\\\= \mathbf{0.9825}

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