Difference between revisions of "Aufgaben:Exercise 2.1: Election Demand"

From LNTwww
 
(5 intermediate revisions by 2 users not shown)
Line 4: Line 4:
  
 
[[File:EN_Sto_A_2_1_.png|right|frame|Result of election demand]]
 
[[File:EN_Sto_A_2_1_.png|right|frame|Result of election demand]]
In an election, the three candidates  $A$,  $B$  and  $C$  are running for mayor.  
+
In an election,  the three candidates  $A$,  $B$,  $C$  are running for mayor.  
 
*The candidate who receives more than  $50\%$  of the votes cast is elected.  
 
*The candidate who receives more than  $50\%$  of the votes cast is elected.  
*If none of the three candidates succeeds in the first ballot, a run-off election shall be held between the two candidates with the most votes.
+
*If none of the three candidates succeeds in the first ballot,  a runoff election shall be held between the two candidates with the most votes.
  
  
Immediately after the closing of the polling stations, the result of an election demand shall be presented:
+
Immediately after the closing of the polling stations,  the result of an election demand shall be presented:
  
 
:Candidate  $A$:   $48\%$,       Candidate  $B$:   $30\%$,       Candidate  $C$:   $22\%$.  
 
:Candidate  $A$:   $48\%$,       Candidate  $B$:   $30\%$,       Candidate  $C$:   $22\%$.  
Line 15: Line 15:
 
This demand is based on a survey of only  $N = 2000$  of the total  $N' = 800 \hspace{0.05cm}000$  voters.  
 
This demand is based on a survey of only  $N = 2000$  of the total  $N' = 800 \hspace{0.05cm}000$  voters.  
  
In answering the following questions, assume the following:
+
In answering the following questions,  assume the following:
  
 
*The actual (percentage) votes obtained in the election by candidates  $A$,  $B$  and  $C$  can be taken as the probabilities  $p_{\rm A}$,  $p_{\rm B}$  and  $p_{\rm C}$  although these are also themselves determined as relative frequencies  $($related to  $N')$  .
 
*The actual (percentage) votes obtained in the election by candidates  $A$,  $B$  and  $C$  can be taken as the probabilities  $p_{\rm A}$,  $p_{\rm B}$  and  $p_{\rm C}$  although these are also themselves determined as relative frequencies  $($related to  $N')$  .
Line 30: Line 30:
 
*The exercise belongs to the chapter  [[Theory_of_Stochastic_Signals/From_Random_Experiment_to_Random_Variable|From Random Experiment to Random Variable]].
 
*The exercise belongs to the chapter  [[Theory_of_Stochastic_Signals/From_Random_Experiment_to_Random_Variable|From Random Experiment to Random Variable]].
 
   
 
   
*The topic of this chapter is illustrated with examples in the   (German language)   learning video  [[Bernoullisches_Gesetz_der_großen_Zahlen_(Lernvideo)|Bernoullisches Gesetz der großen Zahlen]]  $\Rightarrow$   Bernoulli's Law of Large Numbers.
+
*The topic of this chapter is illustrated with examples in the   (German language)   learning video 
 +
:[[Bernoullisches_Gesetz_der_großen_Zahlen_(Lernvideo)|Bernoullisches Gesetz der großen Zahlen]]  $\Rightarrow$   Bernoulli's Law of Large Numbers.
  
  
Line 37: Line 38:
  
 
<quiz display=simple>
 
<quiz display=simple>
{Wen erwarten Sie nach dieser Nachfrage als zuk&uuml;nftigen B&uuml;rgermeister?
+
{Who do you expect as future mayor after this demand?
 
|type="[]"}
 
|type="[]"}
+ Kandidat&nbsp; $A$,
+
+ Candidate&nbsp; $A$,
- Kandidat&nbsp; $B$,
+
- candidate&nbsp; $B$,
- Kandidat&nbsp; $C$.
+
- candidate&nbsp; $C$.
  
  
{Wie gro&szlig; ist die Wahrscheinlichkeit, dass keine Stichwahl erforderlich sein wird?&nbsp; Geben Sie hierf&uuml;r die obere Schranke an.
+
{What is the probability that no runoff will be required?&nbsp; Specify the upper bound here.
 
|type="{}"}
 
|type="{}"}
$\text{Maximum:   Pr(keine Stichwahl)} \ = \ $ { 15.6 3% } $\ \rm \%$
+
$\text{Maximum: Pr(no runoff)} \ = \ $ { 15.6 3% } $\ \rm \%$
  
  
{Wir setzen nun voraus, dass Kandidat&nbsp; $A$&nbsp; tats&auml;chlich genau&nbsp; $48\%$&nbsp; der Stimmen erh&auml;lt. <br>Wie gro&szlig; ist damit (h&ouml;chstens) die Wahrscheinlichkeit, dass Kandidat&nbsp; $C$&nbsp; die Stichwahl erreicht?
+
{We now assume that candidate&nbsp; $A$&nbsp; actually receives exactly&nbsp; $48\%$&nbsp; of the votes. <br>What is the probability&nbsp; (at most)&nbsp; that candidate&nbsp; $C$&nbsp; will reach the runoff?
 
|type="{}"}
 
|type="{}"}
$\text{Maximum:   Pr(}C \ \text{in Stichwahl)}\ = \ $ { 3.9 3% } $\ \rm \%$
+
$\text{Maximum: Pr(}C \ \text{in runoff)}\ = \ $ { 3.9 3% } $\ \rm \%$
  
  
Line 57: Line 58:
 
</quiz>
 
</quiz>
  
===Musterlösung===
+
===Solution===
 
{{ML-Kopf}}
 
{{ML-Kopf}}
'''(1)'''&nbsp; Man sollte dieser Nachfrage zumindest glauben, dass&nbsp; $\underline{\text{Kandidat} \ A}$&nbsp; wahrscheinlich gewinnt.
+
'''(1)'''&nbsp; One should at least believe this demand that&nbsp; $\underline{\text{candidate} \ A}$&nbsp; is likely to win.
  
  
'''(2)'''&nbsp; Die Wahrscheinlichkeit, dass die Nachfrage&nbsp; $(h_{\rm A})$&nbsp; vom endg&uuml;ltigen Ergebnis&nbsp; $(p_{\rm A})$&nbsp; betragsm&auml;&szlig;ig um mehr als&nbsp; $2\%$&nbsp; abweicht, ist nach dem Bernouillischen Gesetz der gro&szlig;en Zahlen mit&nbsp; $N = 2000$:
+
'''(2)'''&nbsp; The probability that the demand&nbsp; $(h_{\rm A})$&nbsp; differs from the final outcome&nbsp; $(p_{\rm A})$&nbsp; by more than&nbsp; $2\%$&nbsp; is, according to Bernoulli's law of large numbers,&nbsp; with&nbsp; $N = 2000$:
:$${\rm Pr}(|h_{\rm A} - p_{\rm A}| \geq 0.02) \leq \frac{1}{4 \cdot 2000\cdot 0.02^2} = 0.3125.$$
+
$${\rm Pr}(|h_{\rm A} - p_{\rm A}| \geq 0.02) \leq \frac{1}{4 \cdot 2000\cdot 0.02^2} = 0.3125.$$
*Diese Wahrscheinlichkeit beinhaltet die beiden gleichwahrscheinlichen F&auml;lle, dass&nbsp; $p_{\rm A} \le 46\%$&nbsp; und&nbsp; $p_{\rm A} \ge 50\%$&nbsp; ist.  
+
*This probability includes the two equally likely cases that&nbsp; $p_{\rm A} \le 46\%$&nbsp; and&nbsp; $p_{\rm A} \ge 50\%$&nbsp; is.  
*Nur im letzten Fall gibt es keine Stichwahl:
+
*Only in the last case there is no runoff:
:$${\rm Pr(keine\hspace{0.1cm}Stichwahl)} \le 0.156 \hspace{0.15cm}\underline{=15.6 \%}.$$
+
:$${\rm Pr(no\hspace{0.1cm}runoff)} \le 0.156 \hspace{0.15cm}\underline{=15.6 \%}.$$
  
  
'''(3)'''&nbsp; Mit&nbsp; $\varepsilon = 4\%$&nbsp; $($ergibt sich aus&nbsp; $0.26 -0.22)$&nbsp; liefert das Gesetz der gro&szlig;en Zahlen:
+
'''(3)'''&nbsp; With&nbsp; $\varepsilon = 4\%$&nbsp; $($is given by&nbsp; $0.26 -0.22)$&nbsp; yields the law of large numbers:
 
:$${\rm Pr}\left(|h_{\rm C}-p_{\rm C}|\ge 0.04\right)\le\rm\frac{1}{4\cdot 2000\cdot 0.04^2}=0.078.$$
 
:$${\rm Pr}\left(|h_{\rm C}-p_{\rm C}|\ge 0.04\right)\le\rm\frac{1}{4\cdot 2000\cdot 0.04^2}=0.078.$$
Daraus folgt:  
+
It follows that:  
*Die Wahrscheinlichkeit, dass Kandidat&nbsp; $C$&nbsp; mindestens&nbsp; $26\%$&nbsp; der Stimmen erh&auml;lt, ist nicht gr&ouml;&szlig;er als&nbsp; $3.9\%$.
+
*The probability that candidate&nbsp; $C$&nbsp; receives at least&nbsp; $26\%$&nbsp; of the votes is not greater than&nbsp; $3.9\%$.
*Da&nbsp; $p_{\rm A} = 0.48$&nbsp; fest vorausgesetzt wurde, gilt in diesem Fall gleichzeitig&nbsp; $p_{\rm B} \le 0.26$.  
+
*Since&nbsp; $p_{\rm A} = 0.48$&nbsp; was assumed fixed, in this case simultaneously&nbsp; $p_{\rm B} \le 0.26$.  
*Da es sich hier um kontinuierliche Zufallsgr&ouml;&szlig;en handelt, sind&nbsp; $(p_{\rm C} \ge 0.26, \; p_{\rm B} \le 0.26)$&nbsp; und&nbsp; $(p_{\rm C} > 0.26, \; p_{\rm B}< 0.26)$&nbsp; gleich.  
+
*Since these are continuous random variables,&nbsp; $(p_{\rm C} \ge 0.26, \; p_{\rm B} \le 0.26)$&nbsp; and&nbsp; $(p_{\rm C} > 0.26, \; p_{\rm B}< 0.26)$&nbsp; are equal.  
*Damit ist die Wahrscheinlichkeit, dass&nbsp; $C$&nbsp; die Stichwahl erreicht,  ebenfalls auf&nbsp; $3.9\%$&nbsp; beschr&auml;nkt:
+
*Thus, the probability that&nbsp; $C$&nbsp; reaches the runoff is also limited to&nbsp; $3.9\%$&nbsp; :
:$${\rm Pr(}C\rm \hspace{0.1cm}erreicht\hspace{0.1cm}Stichwahl)\le 0.039 \hspace{0.15cm}\underline{= 3.9 \%}.$$
+
:$${\rm Pr(}C\rm \hspace{0.1cm}reaches\hspace{0.1cm}runoff \hspace{0.1cm}election)\le 0.039 \hspace{0.15cm}\underline{= 3.9 \%}.$$
 
{{ML-Fuß}}
 
{{ML-Fuß}}
  
  
 
[[Category:Theory of Stochastic Signals: Exercises|^2.1 From Experiment to Random Variable^]]
 
[[Category:Theory of Stochastic Signals: Exercises|^2.1 From Experiment to Random Variable^]]

Latest revision as of 13:31, 3 December 2021

Result of election demand

In an election,  the three candidates  $A$,  $B$,  $C$  are running for mayor.

  • The candidate who receives more than  $50\%$  of the votes cast is elected.
  • If none of the three candidates succeeds in the first ballot,  a runoff election shall be held between the two candidates with the most votes.


Immediately after the closing of the polling stations,  the result of an election demand shall be presented:

Candidate  $A$:   $48\%$,       Candidate  $B$:   $30\%$,       Candidate  $C$:   $22\%$.

This demand is based on a survey of only  $N = 2000$  of the total  $N' = 800 \hspace{0.05cm}000$  voters.

In answering the following questions,  assume the following:

  • The actual (percentage) votes obtained in the election by candidates  $A$,  $B$  and  $C$  can be taken as the probabilities  $p_{\rm A}$,  $p_{\rm B}$  and  $p_{\rm C}$  although these are also themselves determined as relative frequencies  $($related to  $N')$  .
  • The  $2000$  selected voters ideally represent the entire electorate in a statistical sense and answered truthfully when asked to vote.
  • According to Bernoulli's Law of Large Numbers  the results of this demand are to be understood as relative frequencies:
$$h_{\rm A} = 0.48,\hspace{0.8cm}h_{\rm B} = 0.30,\hspace{0.9cm} h_{\rm C} = 0.22.$$




Hints:

  • The topic of this chapter is illustrated with examples in the  (German language)  learning video 
Bernoullisches Gesetz der großen Zahlen  $\Rightarrow$   Bernoulli's Law of Large Numbers.


Questions

1

Who do you expect as future mayor after this demand?

Candidate  $A$,
candidate  $B$,
candidate  $C$.

2

What is the probability that no runoff will be required?  Specify the upper bound here.

$\text{Maximum: Pr(no runoff)} \ = \ $

$\ \rm \%$

3

We now assume that candidate  $A$  actually receives exactly  $48\%$  of the votes.
What is the probability  (at most)  that candidate  $C$  will reach the runoff?

$\text{Maximum: Pr(}C \ \text{in runoff)}\ = \ $

$\ \rm \%$


Solution

(1)  One should at least believe this demand that  $\underline{\text{candidate} \ A}$  is likely to win.


(2)  The probability that the demand  $(h_{\rm A})$  differs from the final outcome  $(p_{\rm A})$  by more than  $2\%$  is, according to Bernoulli's law of large numbers,  with  $N = 2000$: $${\rm Pr}(|h_{\rm A} - p_{\rm A}| \geq 0.02) \leq \frac{1}{4 \cdot 2000\cdot 0.02^2} = 0.3125.$$

  • This probability includes the two equally likely cases that  $p_{\rm A} \le 46\%$  and  $p_{\rm A} \ge 50\%$  is.
  • Only in the last case there is no runoff:
$${\rm Pr(no\hspace{0.1cm}runoff)} \le 0.156 \hspace{0.15cm}\underline{=15.6 \%}.$$


(3)  With  $\varepsilon = 4\%$  $($is given by  $0.26 -0.22)$  yields the law of large numbers:

$${\rm Pr}\left(|h_{\rm C}-p_{\rm C}|\ge 0.04\right)\le\rm\frac{1}{4\cdot 2000\cdot 0.04^2}=0.078.$$

It follows that:

  • The probability that candidate  $C$  receives at least  $26\%$  of the votes is not greater than  $3.9\%$.
  • Since  $p_{\rm A} = 0.48$  was assumed fixed, in this case simultaneously  $p_{\rm B} \le 0.26$.
  • Since these are continuous random variables,  $(p_{\rm C} \ge 0.26, \; p_{\rm B} \le 0.26)$  and  $(p_{\rm C} > 0.26, \; p_{\rm B}< 0.26)$  are equal.
  • Thus, the probability that  $C$  reaches the runoff is also limited to  $3.9\%$  :
$${\rm Pr(}C\rm \hspace{0.1cm}reaches\hspace{0.1cm}runoff \hspace{0.1cm}election)\le 0.039 \hspace{0.15cm}\underline{= 3.9 \%}.$$