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

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{{quiz-Header|Buchseite=Stochastische Signaltheorie/Poissonverteilung
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{{quiz-Header|Buchseite=Theory_of_Stochastic_Signals/Poisson_Distribution
 
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}}
  
[[File:P_ID104__Sto_A_2_5_neu.png|right|Binomial- oder poissonverteilt?]]
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[[File:P_ID104__Sto_A_2_5_neu.png|right|frame|Characteristics of  $z_1$  and  $z_2$]]
Betrachtet werden zwei diskrete Zufallsgrößen $z_1$ und $z_2$, die alle ganzzahligen Werte zwischen $0$ und $5$ (einschließlich dieser Grenzen) annehmen können. Die Wahrscheinlichkeiten dieser Zufallsgrößen sind in nebenstehender Tabelle angegeben. Eine der beiden Zufallsgrößen ist allerdings nicht auf den angegebenen Wertebereich begrenzt.
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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).  
  
Weiterhin ist bekannt, dass
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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.
  
* eine der Größen binomialverteilt ist, und
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Furthermore it is known that
  
* die andere eine Poissonverteilung beschreibt.
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* one of the variables is binomially distributed,  and
  
 +
* the other describes a Poisson distribution.
  
Nicht bekannt ist allerdings, welche der beiden Zufallsgrößen $z_1$ und $z_2$ binomialverteilt und welche poissonverteilt  ist.
 
  
 +
However,  it is not known which of the two variables  $(z_1$  or $z_2)$  is binomially distributed and which is Poisson distributed.
  
''Hinweise:''
 
*Die Aufgabe gehört zum  Kapitel [[Stochastische_Signaltheorie/Poissonverteilung|Poissonverteilung]].
 
*Bezug genommen wird aber auch auf das vorherige  Kapitel [[Stochastische_Signaltheorie/Binomialverteilung|Binomialverteilung]].
 
*Sollte die Eingabe des Zahlenwertes „0” erforderlich sein, so geben Sie bitte „0.” ein.
 
  
  
  
===Fragebogen===
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 +
 
 +
Hints:
 +
*This exercise belongs to the chapter  [[Theory_of_Stochastic_Signals/Poisson_Distribution|Poisson distribution]].
 +
*But also refers to the previous chapter  [[Theory_of_Stochastic_Signals/Binomial_Distribution|Binomial Distribution]].
 +
*To check your results you can use the interactive HTML5/JavaScript applet  [[Applets:Binomial_and_Poisson_Distribution_(Applet)|Binomial and Poisson distribution]].
 +
 +
 
 +
 
 +
 
 +
 
 +
 
 +
===Questions===
  
 
<quiz display=simple>
 
<quiz display=simple>
{Ermitteln Sie aus den Wahrscheinlichkeiten, den Mittelwerten und den Streuungen, ob <i>z</i><sub>1</sub> oder <i>z</i><sub>2</sub> poissonverteilt ist.
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{Find out from the probabilities,&nbsp; means,&nbsp; and standard deviations whether&nbsp; $z_1$&nbsp; or&nbsp; $z_2$&nbsp; is Poisson distributed.
|type="[]"}
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|type="()"}
+ <i>z</i><sub>1</sub> ist poissonverteilt und <i>z</i><sub>2</sub> ist binomialverteilt.
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+ $z_1$&nbsp; is Poisson distributed and&nbsp; $z_2$&nbsp; is binomially distributed.
- <i>z</i><sub>1</sub> ist binomialverteilt und <i>z</i><sub>2</sub> ist poissonverteilt.
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- $z_1$&nbsp; is binomially distributed and&nbsp; $z_2$&nbsp; is Poisson distributed.
  
  
{Welche Rate <i>&lambda;</i> weist die Poissonverteilung auf?
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{What rate&nbsp; $\lambda$&nbsp; does the Poisson distribution exhibit?
 
|type="{}"}
 
|type="{}"}
$\lambda$ = { 2 3% }
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$\lambda \ = \ $ { 2 3% }
  
  
{Die Werte der Poissonverteilung sind nicht auf 0....5 begrenzt. Wie gro&szlig; ist die Wahrscheinlichkeit, dass die unter a) ermittelte Gr&ouml;&szlig;e gleich „6“ ist?
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{The values of the Poisson distribution are not limited to the range&nbsp; $0$, ... , $5$&nbsp;. <br>What are the probabilities that the Poisson distributed size is exactly equal to&nbsp; $6$&nbsp; or is greater than&nbsp; $6$&nbsp;?
 
|type="{}"}
 
|type="{}"}
$Pr(6)$ = { 0.012 3% }
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${\rm Pr}(z_{\rm Poisson} = 6) \ = \ $ { 0.012 3% }
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${\rm Pr}(z_{\rm Poisson} > 6) \ = \ $ { 0.004 3% }
  
  
{Betrachten Sie nun die Binomialverteilung. Berechnen Sie aus deren Mittelwert und Streuung die charakteristische Wahrscheinlichkeit <i>p</i>.
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{Now consider the binomial distribution.&nbsp; Give its characteristic probability&.
 
|type="{}"}
 
|type="{}"}
$p$ = { 0.4 3% }
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$p \ = \ $ { 0.4 3% }
  
  
{Wie gro&szlig; ist damit der Parameter <i>I</i> der Binomialverteilung? &Uuml;berpr&uuml;fen Sie Ihr Ergebnis anhand der Wahrscheinlichkeit Pr(0).
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{What is the size of the parameter&nbsp; $I$&nbsp; of the binomial distribution?&nbsp; Check your result using the probability&nbsp; $\rm Pr(0)$.
 
|type="{}"}
 
|type="{}"}
$I$ = { 5 3% }
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$I \ = \ $ { 5 3% }
 
 
  
  
 
</quiz>
 
</quiz>
  
===Musterlösung===
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===Solution===
 
{{ML-Kopf}}
 
{{ML-Kopf}}
:<b>1.</b>&nbsp;&nbsp;Bei der Poissonverteilung sind Mittelwert <i>m</i><sub>1</sub> und Varianz <i>&sigma;</i><sup>2</sup> gleich. Die Zufallsgröße <i>z</i><sub>1</sub> erf&uuml;llt diese Bedingung &nbsp;&#8658;&nbsp; <u>Lösungsvorschlag 1</u>.
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'''(1)'''&nbsp; Correct is the <u>proposed solution 1</u>:
 +
*In the Poisson distribution,&nbsp; mean&nbsp; $m_1$&nbsp; and variance&nbsp; $\sigma^2$&nbsp; are equal.
 +
*The random variable&nbsp; $z_1$&nbsp; satisfies this condition in contrast to the random variable&nbsp; $z_2$.
 +
 
 +
 
 +
 
 +
'''(2)'''&nbsp; Moreover,&nbsp; in the Poisson distribution,&nbsp; the mean is equal to the rate.&nbsp; Therefore,&nbsp; $\underline{\lambda = 2}$&nbsp; must hold.
 +
 
  
:<b>2.</b>&nbsp;&nbsp;Bei der Poissonverteilung ist der Mittelwert auch gleich der Rate. Deshalb muss <u><i>&lambda;</i> = 2</u> gelten.
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'''(3)'''&nbsp; The corresponding probability is with&nbsp; $z_{\rm Poisson} = z_1$:
 +
:$${\rm Pr}(z_1 = 6)=\frac{2^6}{6!}\cdot e^{-2}\hspace{0.15cm} \underline{\approx 0.012}$$
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:$${\rm Pr}(z_1 > 6)=1 -{\rm Pr}(0) -{\rm Pr}(1) - \ \text{...} \ -{\rm Pr}(6)\hspace{0.15cm} \underline{\approx 0.004}.$$
  
:<b>3.</b>&nbsp;&nbsp;Die entsprechende Wahrscheinlichkeit lautet:
 
:$$\rm Pr(z_1 = 6)=\frac{2^6}{6!}\cdot e^{-2}\hspace{0.15cm} \underline{=0.012}.$$
 
  
:Die Wahrscheinlichkeit Pr(<i>z</i><sub>1</sub> > 6) ergibt sich zu 1 &ndash; Pr(0) &ndash; Pr(1) &ndash;  ... &ndash; Pr(6). Es ergibt sich der Zahlenwert Pr(<i>z</i><sub>1</sub> > 6) &asymp; 0.004.
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'''(4)'''&nbsp; For the variance of the binomial distribution holds:
 +
:$$\sigma^{2}= I\cdot p\cdot (1- p)= m_{\rm 1}\cdot ( 1- p).$$
  
:<b>4.</b>&nbsp;&nbsp;F&uuml;r die Varianz der Binomialverteilung gilt:
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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:
:$$\sigma^{\rm 2}=\it I\cdot p\cdot (\rm 1-\it p)=\it m_{\rm 1}\cdot (\rm 1-\it p).$$
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:$$ 1- p = \frac{\sigma^{2}}{m_1}= \frac{1.2}{2} = 0.6\hspace{0.3cm}\Rightarrow \hspace{0.3cm} p \hspace{0.15cm} \underline{= 0.4}.$$
  
:Die charakteristische Wahrscheinlichkeit der Binomialverteilung ergibt sich damit aus der Varianz <nobr>1.095<sup>2</sup> = 1.2</nobr> und dem Mittelwert 2 entsprechend der Gleichung:
 
:$$ 1- p = \frac{\sigma^{2}}{m_1}=  \frac{1.2}{2} = 0.6\hspace{0.3cm}\Rightarrow \hspace{0.3cm} p \hspace{0.15cm} \underline{= 0.4}.$$
 
  
:<b>5.</b>&nbsp;&nbsp;Aus dem Mittelwert <i>m</i><sub>1</sub> = 2 folgt weiterhin <u><i>I</i> = 5</u>. Die Wahrscheinlichkeit f&uuml;r den Wert &bdquo;0&rdquo; m&uuml;sste mit diesen Parametern wie folgt lauten:
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'''(5)'''&nbsp; From the mean&nbsp; $m_1 = 2$&nbsp; it further follows&nbsp; $\underline{I= 5}.$
:$$\rm Pr(z_2 = 0)=\left({5 \atop {0}}\right)\cdot \it p^{\rm 0}\cdot (\rm 1 -\it p)^{\rm 5-0}=\rm 0.6^5=0.078.$$
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*The probability for the outcome&nbsp; "0"&nbsp; would have to be as follows with these parameters:
 +
:$${\rm Pr}(z_2 = 0)=\left({5 \atop {0}}\right)\cdot p^{\rm 0}\cdot (1 - p)^{\rm 5-0}=0.6^5=0.078.$$
  
:Das bedeutet: Das Ergebnis ist richtig.
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*This means: &nbsp; <u>Our results are correct</u>.
 
{{ML-Fuß}}
 
{{ML-Fuß}}
  
  
  
[[Category:Aufgaben zu Stochastische Signaltheorie|^2.4 Poissonverteilung^]]
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[[Category:Theory of Stochastic Signals: Exercises|^2.4 Poisson Distribution^]]

Latest revision as of 15:10, 16 February 2022

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 standard deviations 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 for the outcome  "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.