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

From LNTwww
m (Text replacement - "”" to """)
 
(7 intermediate revisions by 2 users not shown)
Line 1: Line 1:
  
{{quiz-Header|Buchseite=Stochastische Signaltheorie/Poissonverteilung
+
{{quiz-Header|Buchseite=Theory_of_Stochastic_Signals/Poisson_Distribution
 
}}
 
}}
  
[[File:P_ID104__Sto_A_2_5_neu.png|right|frame|Kenngrößen von  $z_1$  und  $z_2$]]
+
[[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 (mindestens) 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.
+
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
+
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
+
Furthermore it is known that
  
* die andere eine Poissonverteilung beschreibt.
+
* one of the variables is binomially distributed,  and
  
 +
* the other describes a Poisson distribution.
  
Nicht bekannt ist allerdings, welche der beiden Größen  $(z_1$  oder  $z_2)$  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.
  
  
Line 21: Line 22:
  
  
 
+
Hints:  
''Hinweise:''
+
*This exercise belongs to the chapter  [[Theory_of_Stochastic_Signals/Poisson_Distribution|Poisson distribution]].
*Die Aufgabe gehört zum  Kapitel  [[Theory_of_Stochastic_Signals/Poissonverteilung|Poissonverteilung]].
+
*But also refers to the previous chapter  [[Theory_of_Stochastic_Signals/Binomial_Distribution|Binomial Distribution]].
*Bezug genommen wird aber auch auf das vorherige  Kapitel  [[Theory_of_Stochastic_Signals/Binomialverteilung|Binomialverteilung]].
+
*To check your results you can use the interactive HTML5/JavaScript applet  [[Applets:Binomial_and_Poisson_Distribution_(Applet)|Binomial and Poisson distribution]].
*Zur Kontrolle Ihrer Ergebnisse können Sie das interaktive Applet  [[Applets:Binomial-_und_Poissonverteilung_(Applet)|Binomial– und Poissonverteilung]]  benutzen.
 
 
   
 
   
  
Line 32: Line 32:
  
  
===Fragebogen===
+
===Questions===
  
 
<quiz display=simple>
 
<quiz display=simple>
{Ermitteln Sie aus den Wahrscheinlichkeiten, den Mittelwerten und den Streuungen, ob&nbsp; $z_1$&nbsp; oder&nbsp; $z_2$&nbsp; poissonverteilt ist.
+
{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="[]"}
+
|type="()"}
+ $z_1$&nbsp; ist poissonverteilt und&nbsp; $z_2$&nbsp; ist binomialverteilt.
+
+ $z_1$&nbsp; is Poisson distributed and&nbsp; $z_2$&nbsp; is binomially distributed.
- $z_1$&nbsp; ist binomialverteilt und&nbsp; $z_2$&nbsp; ist poissonverteilt.
+
- $z_1$&nbsp; is binomially distributed and&nbsp; $z_2$&nbsp; is Poisson distributed.
  
  
{Welche Rate&nbsp; $\lambda$&nbsp; weist die Poissonverteilung auf?
+
{What rate&nbsp; $\lambda$&nbsp; does the Poisson distribution exhibit?
 
|type="{}"}
 
|type="{}"}
$\lambda \ = \ $ { 2 3% }
+
$\lambda \ = \ $ { 2 3% }
  
  
{Die Werte der Poissonverteilung sind nicht auf den Bereich&nbsp; $0$, ... , $5$&nbsp; begrenzt. <br>Wie gro&szlig; sind die Wahrscheinlichkeiten, dass die poissonverteilte Gr&ouml;&szlig;e exakt gleich&nbsp; $6$&nbsp; ist bzw. größer als&nbsp; $6$&nbsp; ist?
+
{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="{}"}
 
${\rm Pr}(z_{\rm Poisson} = 6) \ = \ $ { 0.012 3% }
 
${\rm Pr}(z_{\rm Poisson} = 6) \ = \ $ { 0.012 3% }
Line 52: Line 52:
  
  
{Betrachten Sie nun die Binomialverteilung.&nbsp; Geben Sie deren charakteristische Wahrscheinlichkeit&nbsp; $p$&nbsp; an.
+
{Now consider the binomial distribution.&nbsp; Give its characteristic probability&.
 
|type="{}"}
 
|type="{}"}
 
$p \ = \ $ { 0.4 3% }
 
$p \ = \ $ { 0.4 3% }
  
  
{Wie gro&szlig; ist damit der Parameter&nbsp; $I$&nbsp; der Binomialverteilung?&nbsp; &Uuml;berpr&uuml;fen Sie Ihr Ergebnis anhand der Wahrscheinlichkeit&nbsp; $\rm Pr(0)$.
+
{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% }
 
$I \ = \ $ { 5 3% }
 
  
  
 
</quiz>
 
</quiz>
  
===Musterlösung===
+
===Solution===
 
{{ML-Kopf}}
 
{{ML-Kopf}}
'''(1)'''&nbsp; Richtig ist der <u>Lösungsvorschlag 1</u>:
+
'''(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.  
+
*In the Poisson distribution,&nbsp; 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; $z_2$.
+
*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.
 
  
 +
'''(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.
  
'''(3)'''&nbsp; Die entsprechende Wahrscheinlichkeit lautet mit&nbsp; $z_{\rm Poisson} = z_1$:
+
 
 +
'''(3)'''&nbsp; The corresponding probability is with&nbsp; $z_{\rm Poisson} = z_1$:
 
:$${\rm Pr}(z_1 = 6)=\frac{2^6}{6!}\cdot e^{-2}\hspace{0.15cm} \underline{\approx 0.012}$$
 
:$${\rm Pr}(z_1 = 6)=\frac{2^6}{6!}\cdot e^{-2}\hspace{0.15cm} \underline{\approx 0.012}$$
:$${\rm Pr}(z_1 > 6)=1 -{\rm Pr}(0) -{\rm Pr}(1) - \ \text{...} \ - {\rm Pr}(6)\hspace{0.15cm} \underline{\approx 0.004}.$$
+
:$${\rm Pr}(z_1 > 6)=1 -{\rm Pr}(0) -{\rm Pr}(1) - \ \text{...} \ -{\rm Pr}(6)\hspace{0.15cm} \underline{\approx 0.004}.$$
  
'''(4)'''&nbsp; F&uuml;r die Varianz der Binomialverteilung gilt:
+
 
 +
'''(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:
+
*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:
:$$ 1- p = \frac{\sigma^{2}}{m_1}=   \frac{1.2}{2} = 0.6\hspace{0.3cm}\Rightarrow \hspace{0.3cm} p \hspace{0.15cm} \underline{= 0.4}.$$
+
:$$ 1- p = \frac{\sigma^{2}}{m_1}= \frac{1.2}{2} = 0.6\hspace{0.3cm}\Rightarrow \hspace{0.3cm} p \hspace{0.15cm} \underline{= 0.4}.$$
 +
 
  
'''(5)'''&nbsp; Aus dem Mittelwert&nbsp; $m_1 = 2$&nbsp; folgt weiterhin&nbsp; $\underline{I= 5}.$  
+
'''(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:
+
*The probability for the outcome&nbsp; "0"&nbsp; would have to be as follows with these parameters:
:$${\rm Pr}(z_2 = 0)=\left({5 \atop {0}}\right)\cdot p^{\rm 0}\cdot (1 - p)^{\rm 5-0}=0.6^5=0.078.$$
+
:$${\rm Pr}(z_2 = 0)=\left({5 \atop {0}}\right)\cdot p^{\rm 0}\cdot (1 - p)^{\rm 5-0}=0.6^5=0.078.$$
  
*Das bedeutet: &nbsp; <u>Unsere Ergebnisse sind richtig</u>.
+
*This means: &nbsp; <u>Our results are correct</u>.
 
{{ML-Fuß}}
 
{{ML-Fuß}}
  
  
  
[[Category:Theory of Stochastic Signals: Exercises|^2.4 Poissonverteilung^]]
+
[[Category:Theory of Stochastic Signals: Exercises|^2.4 Poisson Distribution^]]

Latest revision as of 16:10, 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.