Difference between revisions of "Aufgaben:Exercise 2.5: "Binomial" or "Poisson"?"

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</quiz>
 
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===Musterlösung===
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===Solution===
 
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'''(1)'''&nbsp; Richtig ist der <u>Lösungsvorschlag 1</u>:
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'''(1)'''&nbsp; Correct is the <u>proposed solution 1</u>:
*Bei der Poissonverteilung sind Mittelwert&nbsp; $m_1$&nbsp; und Varianz&nbsp; $\sigma^2$&nbsp; gleich.  
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*In the Poisson distribution, mean&nbsp; $m_1$&nbsp; and variance&nbsp; $\sigma^2$&nbsp; are equal.  
*Die Zufallsgröße&nbsp; $z_1$&nbsp; erf&uuml;llt diese Bedingung im Gegensatz zur Zufallsgröße&nbsp; $z_2$.
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*The random variable&nbsp; $z_1$&nbsp; satisfies this condition in contrast to the random variable&nbsp; $z_2$.
  
  
'''(2)'''&nbsp; Bei der Poissonverteilung ist zudem der Mittelwert gleich der Rate.&nbsp; Deshalb muss&nbsp; $\underline{\lambda = 2}$&nbsp; gelten.
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'''(2)'''&nbsp; Moreover, in the Poisson distribution, the mean is equal to the rate.&nbsp; Therefore,&nbsp; $\underline{\lambda = 2}$&nbsp; must hold.
  
  
'''(3)'''&nbsp; Die entsprechende Wahrscheinlichkeit lautet mit&nbsp; $z_{\rm Poisson} = z_1$:
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'''(3)'''&nbsp; The corresponding probability is with&nbsp; $z_{\rm Poisson} = z_1$:
 
:$${\rm Pr}(z_1 = 6)=\frac{2^6}{6!}\cdot e^{-2}\hspace{0.15cm} \underline{\approx 0.012}$$
 
:$${\rm Pr}(z_1 = 6)=\frac{2^6}{6!}\cdot e^{-2}\hspace{0.15cm} \underline{\approx 0.012}$$
:$${\rm Pr}(z_1 > 6)=1 -{\rm Pr}(0) -{\rm Pr}(1) - \ \text{...} \ - {\rm Pr}(6)\hspace{0.15cm} \underline{\approx 0.004}.$$
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:$${\rm Pr}(z_1 > 6)=1 -{\rm Pr}(0) -{\rm Pr}(1) - \ \text{...} \ -{\rm Pr}(6)\hspace{0.15cm} \underline{\approx 0.004}.$$
  
'''(4)'''&nbsp; F&uuml;r die Varianz der Binomialverteilung gilt:
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'''(4)'''&nbsp; For the variance of the binomial distribution holds:
 
:$$\sigma^{2}= I\cdot p\cdot (1- p)= m_{\rm 1}\cdot ( 1- p).$$
 
:$$\sigma^{2}= I\cdot p\cdot (1- p)= m_{\rm 1}\cdot ( 1- p).$$
  
*Die charakteristische Wahrscheinlichkeit der Binomialverteilung ergibt sich aus der Varianz&nbsp; $\sigma^2 = 1.095$&nbsp; und dem Mittelwert&nbsp; $m_1 = 2$&nbsp; gemäß der Gleichung:
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*The characteristic probability of the binomial distribution is obtained from the variance&nbsp; $\sigma^2 = 1.095$&nbsp; and the mean&nbsp; $m_1 = 2$&nbsp; according to the equation:
:$$ 1- p = \frac{\sigma^{2}}{m_1}=   \frac{1.2}{2} = 0.6\hspace{0.3cm}\Rightarrow \hspace{0.3cm} p \hspace{0.15cm} \underline{= 0.4}.$$
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:$$ 1- p = \frac{\sigma^{2}}{m_1}= \frac{1.2}{2} = 0.6\hspace{0.3cm}\Rightarrow \hspace{0.3cm} p \hspace{0.15cm} \underline{= 0.4}.$$
  
'''(5)'''&nbsp; Aus dem Mittelwert&nbsp; $m_1 = 2$&nbsp; folgt weiterhin&nbsp; $\underline{I= 5}.$  
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'''(5)'''&nbsp; From the mean&nbsp; $m_1 = 2$&nbsp; it further follows&nbsp; $\underline{I= 5}.$  
*Die Wahrscheinlichkeit f&uuml;r den Wert "0" m&uuml;sste mit diesen Parametern wie folgt lauten:
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*The probability f&uuml;r the value "0" would have to be as follows with these parameters:
:$${\rm Pr}(z_2 = 0)=\left({5 \atop {0}}\right)\cdot p^{\rm 0}\cdot (1 - p)^{\rm 5-0}=0.6^5=0.078.$$
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:$${\rm Pr}(z_2 = 0)=\left({5 \atop {0}}\right)\cdot p^{\rm 0}\cdot (1 - p)^{\rm 5-0}=0.6^5=0.078.$$
  
*Das bedeutet: &nbsp; <u>Unsere Ergebnisse sind richtig</u>.
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*This means: &nbsp; <u>Our results are correct</u>.
 
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Revision as of 01:09, 19 December 2021

Characteristics of  $z_1$  and  $z_2$

Consider two discrete random variables  $z_1$  and  $z_2$  that can take  (at least)  all integer values between  $0$  and  $5$  (including these limits).

The probabilities of these random variables are given in the adjacent table.  However,  one of the two random variables is not limited to the given range of values.

Furthermore it is known that

  • one of the variables is binomially distributed,  and
  • the other describes a Poisson distribution.


However,  it is not known which of the two variables  $(z_1$  or $z_2)$  is binomially distributed and which is Poisson distributed.




Hints:




Questions

1

Find out from the probabilities,  means,  and rms values whether  $z_1$  or  $z_2$  is Poisson distributed.

$z_1$  is Poisson distributed and  $z_2$  is binomially distributed.
$z_1$  is binomially distributed and  $z_2$  is Poisson distributed.

2

What rate  $\lambda$  does the Poisson distribution exhibit?

$\lambda \ = \ $

3

The values of the Poisson distribution are not limited to the range  $0$, ... , $5$ .
What are the probabilities that the Poisson distributed size is exactly equal to  $6$  or is greater than  $6$ ?

${\rm Pr}(z_{\rm Poisson} = 6) \ = \ $

${\rm Pr}(z_{\rm Poisson} > 6) \ = \ $

4

Now consider the binomial distribution.  Give its characteristic probability&.

$p \ = \ $

5

What is the size of the parameter  $I$  of the binomial distribution?  Check your result using the probability  $\rm Pr(0)$.

$I \ = \ $


Solution

(1)  Correct is the proposed solution 1:

  • In the Poisson distribution, mean  $m_1$  and variance  $\sigma^2$  are equal.
  • The random variable  $z_1$  satisfies this condition in contrast to the random variable  $z_2$.


(2)  Moreover, in the Poisson distribution, the mean is equal to the rate.  Therefore,  $\underline{\lambda = 2}$  must hold.


(3)  The corresponding probability is with  $z_{\rm Poisson} = z_1$:

$${\rm Pr}(z_1 = 6)=\frac{2^6}{6!}\cdot e^{-2}\hspace{0.15cm} \underline{\approx 0.012}$$
$${\rm Pr}(z_1 > 6)=1 -{\rm Pr}(0) -{\rm Pr}(1) - \ \text{...} \ -{\rm Pr}(6)\hspace{0.15cm} \underline{\approx 0.004}.$$

(4)  For the variance of the binomial distribution holds:

$$\sigma^{2}= I\cdot p\cdot (1- p)= m_{\rm 1}\cdot ( 1- p).$$
  • The characteristic probability of the binomial distribution is obtained from the variance  $\sigma^2 = 1.095$  and the mean  $m_1 = 2$  according to the equation:
$$ 1- p = \frac{\sigma^{2}}{m_1}= \frac{1.2}{2} = 0.6\hspace{0.3cm}\Rightarrow \hspace{0.3cm} p \hspace{0.15cm} \underline{= 0.4}.$$

(5)  From the mean  $m_1 = 2$  it further follows  $\underline{I= 5}.$

  • The probability für the value "0" would have to be as follows with these parameters:
$${\rm Pr}(z_2 = 0)=\left({5 \atop {0}}\right)\cdot p^{\rm 0}\cdot (1 - p)^{\rm 5-0}=0.6^5=0.078.$$
  • This means:   Our results are correct.