Difference between revisions of "Aufgaben:Exercise 3.2: CDF for Exercise 3.1"

From LNTwww
m (Text replacement - "Category:Aufgaben zu Stochastische Signaltheorie" to "Category:Theory of Stochastic Signals: Exercises")
 
(9 intermediate revisions by 2 users not shown)
Line 1: Line 1:
  
{{quiz-Header|Buchseite=Stochastische Signaltheorie/Verteilungsfunktion (VTF)
+
{{quiz-Header|Buchseite=Theory_of_Stochastic_Signals/Cumulative_Distribution_Function
 
}}
 
}}
  
[[File:P_ID114__Sto_A_3_2.png|right|frame|Cosinus&ndash;Quadrat&ndash;VTF (oben),<br> Dirac&ndash;VTF (unten)]]
+
[[File:P_ID114__Sto_A_3_2.png|right|frame|Given cumulative distribution function&nbsp; $\rm (CDF)$]]
Es gelten die gleichen Voraussetzungen wie für die&nbsp; [[Aufgaben:3.1_cos²_-_und_Dirac-WDF|Aufgabe 3.1]].  
+
The same conditions apply as for&nbsp; [[Aufgaben:Exercise_3.1:_cos²-PDF_and_PDF_with_Dirac_Functions|Exercise 3.1]].  
*Die WDF der wertkontinuierlichen Zufallsgr&ouml;&szlig;e ist in den Bereichen&nbsp; $|x| > 2$&nbsp; identisch Null,&nbsp; und im Bereich&nbsp; $-2 \le x \le +2$&nbsp; gilt:
+
*The PDF of the continuous valued random variable is identically zero in the ranges&nbsp; $|x| > 2$.&nbsp;  
 +
*In the range&nbsp; $-2 \le x \le +2$&nbsp; holds:
 
:$$f_x(x)={1}/{2}\cdot \cos^2({\pi}/{4}\cdot x).$$
 
:$$f_x(x)={1}/{2}\cdot \cos^2({\pi}/{4}\cdot x).$$
  
*Auch die diskrete Zufallsgr&ouml;&szlig;e&nbsp; $y$&nbsp; ist auf den Bereich&nbsp; $\pm 2$&nbsp; begrenzt.&nbsp; Hier gelten folgende Wahrscheinlichkeiten:
+
*The discrete valued random variable&nbsp; $y$&nbsp; is limited too to the range&nbsp; $\pm 2$&nbsp; Here,&nbsp; the following probabilities apply:
 
:$${\rm \Pr}(y=0)=0.4,$$
 
:$${\rm \Pr}(y=0)=0.4,$$
 
:$${\rm \Pr}(y=+1)={\rm \Pr}(y=-1)=0.2,$$
 
:$${\rm \Pr}(y=+1)={\rm \Pr}(y=-1)=0.2,$$
Line 19: Line 20:
  
  
''Hinweise:''
+
Hints:
*Die Aufgabe gehört zum  Kapitel&nbsp; [[Theory_of_Stochastic_Signals/Verteilungsfunktion|Verteilungsfunktion]].
+
*The exercise belongs to the chapter&nbsp; [[Theory_of_Stochastic_Signals/Cumulative_Distribution_Function|Cumulative Distribution Function]].
 +
*The topic of this chapter is illustrated with examples in the&nbsp; (German language)&nbsp; learning video <br> &nbsp; &nbsp; [[Zusammenhang_zwischen_WDF_und_VTF_(Lernvideo)|"Zusammenhang zwischen WDF und VTF"]] &nbsp; $\Rightarrow$ &nbsp; "Relationship between PDF and CDF".
 +
*Given the following equation:
 +
:$$\int \cos^{\rm 2}( ax)\, {\rm d}x=\frac{x}{2}+\frac{1}{4 a}\cdot \sin(2 ax).$$
  
*Gegeben ist die folgende Gleichung:
 
:$$\int \cos^{\rm 2}( ax)\, {\rm d}x=\frac{x}{2}+\frac{1}{4  a}\cdot \sin(2 ax).$$
 
*Eine Zusammenfassung der hier behandelten Thematik bietet das Lernvideo&nbsp; [[Zusammenhang_zwischen_WDF_und_VTF_(Lernvideo)|Zusammenhang zwischen WDF und VTF]].
 
 
  
  
  
===Fragebogen===
+
===Questions===
  
 
<quiz display=simple>
 
<quiz display=simple>
{Welche der folgenden Aussagen sind f&uuml;r die Verteilungsfunktion&nbsp; $F_x(r)$&nbsp; der wertkontinuierlichen Zufallsgr&ouml;&szlig;e&nbsp; $x$&nbsp; richtig?
+
{Which of the following statements are true for the cumulative distribution function&nbsp; $F_x(r)$&nbsp; of the continuous valued random variable&nbsp; $x$&nbsp;?
 
|type="[]"}
 
|type="[]"}
+ Die VTF ist f&uuml;r alle Werte&nbsp; $r \le -2$&nbsp; gleich&nbsp; $F_x(r) \equiv 0$.
+
+ The CDF is equal for all values&nbsp; $r \le -2$ &nbsp; &rArr; &nbsp; $F_x(r) \equiv 0$.
+ Die VTF ist f&uuml;r alle Werte&nbsp; $r \ge +2$&nbsp; gleich&nbsp; $F_x(r) \equiv 1$.
+
+ The CDF is equal for all values&nbsp; $r \ge +2$ &nbsp; &rArr; &nbsp; $F_x(r) \equiv 1$.
+ Der Verlauf von&nbsp; $F_x(r)$&nbsp; ist monoton steigend.
+
+ The curve of&nbsp; $F_x(r)$&nbsp; is monotonically increasing.
  
  
{Welche der folgenden Aussagen sind f&uuml;r die Verteilungsfunktion&nbsp; $F_y(r)$&nbsp; der wertdiskreten Zufallsgr&ouml;&szlig;e&nbsp; $y$&nbsp; richtig?
+
{Which of the following statements are true for the cumulative distribution function&nbsp; $F_y(r)$&nbsp; of the discrete valued random variable&nbsp; $y$&nbsp;?
 
|type="[]"}
 
|type="[]"}
- Die VTF ist f&uuml;r alle Werte&nbsp; $r \le -2$&nbsp; gleich&nbsp; $F_y(r) \equiv 0$.
+
- The CDF is equal for all values&nbsp; $r \le -2$ &nbsp; &rArr; &nbsp; $F_y(r) \equiv 0$.
+ Die VTF ist f&uuml;r alle Werte&nbsp; $r \ge +2$&nbsp; gleich&nbsp; $F_y(r) \equiv 1$.
+
+ The CDF is equal for all values&nbsp; $r \ge +2$ &nbsp; &rArr; &nbsp; $F_y(r) \equiv 1$.
+ Der Verlauf von&nbsp; $F_y(r)$&nbsp; ist monoton steigend.
+
+ The curve of&nbsp; $F_y(r)$&nbsp; is monotonically increasing.
  
  
{Berechnen Sie die Verteilungsfunktion&nbsp; $F_x(r)$.&nbsp; Beschr&auml;nken Sie sich hier auf den Bereich&nbsp; $0 \le r \le +2$. <br>Welcher Wert ergibt sich f&uuml;r&nbsp; $r = +1$?
+
{Calculate the CDF&nbsp; $F_x(r)$.&nbsp; Restrict yourself to the range&nbsp; $0 \le r \le +2$.&nbsp; What value results for&nbsp; $r = +1$?
 
|type="{}"}
 
|type="{}"}
 
$F_x(r=+1) \ = \ $ { 0.909 3% }
 
$F_x(r=+1) \ = \ $ { 0.909 3% }
  
  
{Welcher Zusammenhang besteht zwischen&nbsp; $F_x(r)$&nbsp; und&nbsp; $F_x(-r)$?&nbsp; Geben Sie den VTF-Wert&nbsp; $F_x(r=-1)$&nbsp; ein.
+
{What is the relationship between&nbsp; $F_x(r)$&nbsp; and&nbsp; $F_x(-r)$?&nbsp; Enter the CDF value&nbsp; $F_x(r=-1)$.
 
|type="{}"}
 
|type="{}"}
$F_x(r=-1) \ = \ $ { 0.091 3% }
+
$F_x(r=-1) \ = \ $ { 0.091 3% }
  
  
{Berechnen Sie die Wahrscheinlichkeit, dass&nbsp; $x$&nbsp; betragsm&auml;&szlig;ig kleiner als&nbsp; $1$&nbsp; ist. <br>Vergleichen Sie das Resultat mit dem Ergebnis der Teilaufgabe&nbsp; '''(7)'''&nbsp; von Aufgabe 3.1.
+
 
 +
 
 +
{Calculate the probability that&nbsp; $|\hspace{0.05cm}x\hspace{0.05cm}|$&nbsp; is smaller  than&nbsp; $1$.&nbsp; Compare the result with the result of subtask&nbsp; '''(7)'''&nbsp; of Exercise 3.1.
 
|type="{}"}
 
|type="{}"}
${\rm Pr}(|\hspace{0.05cm}x\hspace{0.05cm}| < 1) \ = \ $ { 0.818 3% }
+
${\rm Pr}(|\hspace{0.05cm}x\hspace{0.05cm}| < 1) \ = \ $ { 0.818 3% }
  
  
{Welchen Wert erh&auml;lt man f&uuml;r die Verteilungsfunktion der diskreten Zufallsgr&ouml;&szlig;e&nbsp; $y$&nbsp; an der Stelle&nbsp; $r = 0$?
+
 
 +
{What value is obtained for the CDF of the discrete valued random variable&nbsp; $y$&nbsp; at the location&nbsp; $r = 0$?
 
|type="{}"}
 
|type="{}"}
$F_y(r = 0)\ = \ $ { 0.7 3% }
+
$F_y(r = 0)\ = \ $ { 0.7 3% }
  
  
Line 70: Line 73:
 
</quiz>
 
</quiz>
  
===Musterlösung===
+
===Solution===
 
{{ML-Kopf}}
 
{{ML-Kopf}}
'''(1)'''&nbsp; Da&nbsp; $x$&nbsp; eine kontinuierliche Zufallsgr&ouml;&szlig;e und auf den Bereich&nbsp; $|\hspace{0.05cm}x\hspace{0.05cm}< 2|$&nbsp;  begrenzt ist, sind <u>alle drei vorgegebenen Aussagen</u> richtig.
+
'''(1)'''&nbsp; Since the continuous valued random variable&nbsp; $x$&nbsp; is limited to the range&nbsp; $|\hspace{0.05cm}x\hspace{0.05cm}< 2|$,&nbsp;  <u>all three given statements</u>&nbsp; are correct.
  
  
  
'''(2)'''&nbsp; Richtig sind hier nur die <u>Aussagen 2 und 3</u>:
+
'''(2)'''&nbsp; Only&nbsp; <u>statements 2 and 3</u>&nbsp; are correct here:
*Bei einer diskreten Zufallsgr&ouml;&szlig;e steigt die Verteilungsfunktion nur schwach monoton an.
+
*For a discrete valued random variable,&nbsp; the cumulative distribution function increases only weakly monotonically.
* Das heißt: &nbsp; Es gibt au&szlig;er Spr&uuml;ngen ausschlie&szlig;lich horizontale Abschnitte der VTF.
+
* That means:&nbsp; Except for unit steps,&nbsp; there are only horizontal sections of the CDF.
*Da an den Sprungstellen jeweils der rechtsseitige Grenzwert gilt, ist demzufolge&nbsp; $F_y(-2) = 0.1$, also ungleich Null.  
+
*Since at the unit step points the right-hand side limit value &nbsp; &rArr; &nbsp; $F_y(-2) = 0.1$,&nbsp; i.e. not equal to zero.  
  
  
  
'''(3)'''&nbsp; Die VTF&nbsp; $F_x(r)$&nbsp; berechnet sich als das Integral von&nbsp; $-\infty$&nbsp; bis&nbsp; $r$&nbsp; &uuml;ber die WDF&nbsp; $f_x(x)$.  
+
'''(3)'''&nbsp; The CDF&nbsp; $F_x(r)$&nbsp; is calculated as the integral from&nbsp; $-\infty$&nbsp; to&nbsp; $r$&nbsp; over the PDF&nbsp; $f_x(x)$.  
  
Aufgrund der Symmetrie kann hierf&uuml;r im Bereich&nbsp; $0 \le r \le +2$&nbsp; geschrieben werden:
+
*Due to symmetry,&nbsp; herefore can be written in the range&nbsp; $0 \le r \le +2$:
:$$F_{x} (r) =\frac{1}{2} + \int_{0}^{r} f_x(x)\;{\rm d}x = \frac{1}{2} + \int_{0}^{ r} {1}/{2}\cdot \cos^2 ({\pi}/{4}\cdot x)\;{\rm d}x.$$
+
:$$F_{x} (r) =\frac{1}{2} + \int_{0}^{r} f_x(x)\;{\rm d}x = \frac{1}{2} + \int_{0}^{ r} {1}/{2}\cdot \cos^2 ({\pi}/{4}\cdot x)\;{\rm d}x.$$
  
In gleicher Weise wie bei der Teilaufgabe&nbsp; '''(7)'''&nbsp; der Aufgabe 3.1 erh&auml;lt man somit:  
+
*In the same way as for the subtask&nbsp; '''(7)'''&nbsp; of Exercise 3.1,&nbsp; we thus obtain:  
:$$F_{x} (r) =\frac{1}{2} + \frac{ r}{ 4} + \frac{1}{2 \pi}  \cdot \sin({\pi}/{2}\cdot r),$$
+
:$$F_{x} (r) =\frac{1}{2} + \frac{ r}{ 4} + \frac{1}{2 \pi}  \cdot \sin({\pi}/{2}\cdot r),$$
 
:$$F_{x} (r=0) =\rm \frac{1}{2} + \rm \frac{1}{2 \pi}  \cdot\rm sin(\rm 0)\hspace{0.15cm}{= 0.500},$$
 
:$$F_{x} (r=0) =\rm \frac{1}{2} + \rm \frac{1}{2 \pi}  \cdot\rm sin(\rm 0)\hspace{0.15cm}{= 0.500},$$
:$$F_{x} (r=1) =\rm \frac{1}{2} + \frac{\rm 1}{\rm 4} + \rm \frac{1}{2 \pi}\cdot   \rm sin({\pi}/{2})\hspace{0.15cm}\underline{=0.909},$$
+
:$$F_{x} (r=1) =\rm \frac{1}{2} + \frac{\rm 1}{\rm 4} + \rm \frac{1}{2 \pi}\cdot \rm sin({\pi}/{2})\hspace{0.15cm}\underline{=0.909},$$
:$$F_{x} (r=2) =\rm \frac{1}{2} + \frac{\rm1}{\rm 2} + \rm \frac{1}{2 \pi} \cdot \rm sin(\pi)\hspace{0.15cm}{= 1.000}.$$
+
:$$F_{x} (r=2) =\rm \frac{1}{2} + \frac{\rm1}{\rm 2} + \rm \frac{1}{2 \pi} \cdot \rm sin(\pi)\hspace{0.15cm}{= 1.000}.$$
  
  
'''(4)'''&nbsp; Aufgrund der Punktsymmetrie um&nbsp; $r=0$&nbsp; &nbsp;bzw.&nbsp; $F_{x} (0) = 1/2$&nbsp; und wegen&nbsp; $\sin(-x) = -\sin(x)$&nbsp; gilt diese Formel im gesamten Bereich, wie die folgende Kontrollrechnung zeigt:
+
'''(4)'''&nbsp; Because of the point symmetry around&nbsp; $r=0$&nbsp; &nbsp;resp.&nbsp; $F_{x} (0) = 1/2$&nbsp; and because of&nbsp; $\sin(-x) = -\sin(x)$&nbsp; this formula holds in the whole domain,&nbsp; as the following control calculation shows:
:$$F_{x} (r=-2) =\rm \frac{1}{2} - \frac{\rm1}{\rm 2} - \rm \frac{1}{2 \pi}  \cdot\rm sin(\pi)=0,$$
+
:$$F_{x} (r=-2) =\rm \frac{1}{2} - \frac{\rm1}{\rm 2} - \rm \frac{1}{2 \pi}  \cdot\rm sin(\pi)=0,$$
:$$F_{x} (r=-1) =\rm \frac{1}{2} - \frac{\rm1}{\rm 4} - \rm \frac{1}{2 \pi}  \cdot\rm sin({\pi}/{2})\hspace{0.15cm}\underline{= 0.091}.$$
+
:$$F_{x} (r=-1) =\rm \frac{1}{2} - \frac{\rm1}{\rm 4} - \rm \frac{1}{2 \pi}  \cdot\rm sin({\pi}/{2})\hspace{0.15cm}\underline{= 0.091}.$$
  
  
'''(5)'''&nbsp; F&uuml;r die Wahrscheinlichkeit, dass&nbsp; $x$&nbsp; zwischen&nbsp; $-1$&nbsp; und&nbsp; $+1$&nbsp; liegt, gilt:
+
'''(5)'''&nbsp; For the probability that&nbsp; $x$&nbsp; lies between&nbsp; $-1$&nbsp; and&nbsp; $+1$:
 
:$${\rm Pr}(|\hspace{0.05cm}x\hspace{0.05cm}|< 1)= F_{x}(+1) - F_{ x}(-1)= 0.909-0.091\hspace{0.15cm}\underline{= 0.818}.$$
 
:$${\rm Pr}(|\hspace{0.05cm}x\hspace{0.05cm}|< 1)= F_{x}(+1) - F_{ x}(-1)= 0.909-0.091\hspace{0.15cm}\underline{= 0.818}.$$
  
*Dieses Ergebnis stimmt exakt mit dem Resultat der Teilaufgabe&nbsp; '''(7)'''&nbsp; der Aufgabe 3.1 &uuml;berein, das durch direkte Integration &uuml;ber die WDF ermittelt wurde.
+
*This result agrees exactly with the result of the subtask&nbsp; '''(7)'''&nbsp; of Exercise 3.1&nbsp; which was obtained by direct integration &uuml;over the WDF.
  
  
'''(6)'''&nbsp; Die VTF der diskreten Zufallsgr&ouml;&szlig;e&nbsp; $y$&nbsp; an der Stelle&nbsp; $y =0$&nbsp; ist die Summe der Wahrscheinlichkeiten von&nbsp; $-2$,&nbsp; $-1$&nbsp; und&nbsp; $0$,&nbsp; also gilt
+
 
 +
'''(6)'''&nbsp; The CDF of the discrete valued random variable&nbsp; $y$&nbsp; at the location&nbsp; $y =0$&nbsp; is the sum of the probabilities of&nbsp; $-2$,&nbsp; $-1$&nbsp; and&nbsp; $0$.&nbsp; So:
 
:$$F_y(r = 0)\hspace{0.15cm}\underline{= 0.7}.$$
 
:$$F_y(r = 0)\hspace{0.15cm}\underline{= 0.7}.$$
 
 
{{ML-Fuß}}
 
{{ML-Fuß}}
  
  
  
[[Category:Theory of Stochastic Signals: Exercises|^3.2 Verteilungsfunktion^]]
+
[[Category:Theory of Stochastic Signals: Exercises|^3.2 Cumulative Distribution Function^]]

Latest revision as of 16:18, 4 January 2022

Given cumulative distribution function  $\rm (CDF)$

The same conditions apply as for  Exercise 3.1.

  • The PDF of the continuous valued random variable is identically zero in the ranges  $|x| > 2$. 
  • In the range  $-2 \le x \le +2$  holds:
$$f_x(x)={1}/{2}\cdot \cos^2({\pi}/{4}\cdot x).$$
  • The discrete valued random variable  $y$  is limited too to the range  $\pm 2$  Here,  the following probabilities apply:
$${\rm \Pr}(y=0)=0.4,$$
$${\rm \Pr}(y=+1)={\rm \Pr}(y=-1)=0.2,$$
$${\rm \Pr}(y=+2)={\rm \Pr}(y=-2)=0.1.$$




Hints:

$$\int \cos^{\rm 2}( ax)\, {\rm d}x=\frac{x}{2}+\frac{1}{4 a}\cdot \sin(2 ax).$$



Questions

1

Which of the following statements are true for the cumulative distribution function  $F_x(r)$  of the continuous valued random variable  $x$ ?

The CDF is equal for all values  $r \le -2$   ⇒   $F_x(r) \equiv 0$.
The CDF is equal for all values  $r \ge +2$   ⇒   $F_x(r) \equiv 1$.
The curve of  $F_x(r)$  is monotonically increasing.

2

Which of the following statements are true for the cumulative distribution function  $F_y(r)$  of the discrete valued random variable  $y$ ?

The CDF is equal for all values  $r \le -2$   ⇒   $F_y(r) \equiv 0$.
The CDF is equal for all values  $r \ge +2$   ⇒   $F_y(r) \equiv 1$.
The curve of  $F_y(r)$  is monotonically increasing.

3

Calculate the CDF  $F_x(r)$.  Restrict yourself to the range  $0 \le r \le +2$.  What value results for  $r = +1$?

$F_x(r=+1) \ = \ $

4

What is the relationship between  $F_x(r)$  and  $F_x(-r)$?  Enter the CDF value  $F_x(r=-1)$.

$F_x(r=-1) \ = \ $

5

Calculate the probability that  $|\hspace{0.05cm}x\hspace{0.05cm}|$  is smaller than  $1$.  Compare the result with the result of subtask  (7)  of Exercise 3.1.

${\rm Pr}(|\hspace{0.05cm}x\hspace{0.05cm}| < 1) \ = \ $

6

What value is obtained for the CDF of the discrete valued random variable  $y$  at the location  $r = 0$?

$F_y(r = 0)\ = \ $


Solution

(1)  Since the continuous valued random variable  $x$  is limited to the range  $|\hspace{0.05cm}x\hspace{0.05cm}< 2|$,  all three given statements  are correct.


(2)  Only  statements 2 and 3  are correct here:

  • For a discrete valued random variable,  the cumulative distribution function increases only weakly monotonically.
  • That means:  Except for unit steps,  there are only horizontal sections of the CDF.
  • Since at the unit step points the right-hand side limit value   ⇒   $F_y(-2) = 0.1$,  i.e. not equal to zero.


(3)  The CDF  $F_x(r)$  is calculated as the integral from  $-\infty$  to  $r$  over the PDF  $f_x(x)$.

  • Due to symmetry,  herefore can be written in the range  $0 \le r \le +2$:
$$F_{x} (r) =\frac{1}{2} + \int_{0}^{r} f_x(x)\;{\rm d}x = \frac{1}{2} + \int_{0}^{ r} {1}/{2}\cdot \cos^2 ({\pi}/{4}\cdot x)\;{\rm d}x.$$
  • In the same way as for the subtask  (7)  of Exercise 3.1,  we thus obtain:
$$F_{x} (r) =\frac{1}{2} + \frac{ r}{ 4} + \frac{1}{2 \pi} \cdot \sin({\pi}/{2}\cdot r),$$
$$F_{x} (r=0) =\rm \frac{1}{2} + \rm \frac{1}{2 \pi} \cdot\rm sin(\rm 0)\hspace{0.15cm}{= 0.500},$$
$$F_{x} (r=1) =\rm \frac{1}{2} + \frac{\rm 1}{\rm 4} + \rm \frac{1}{2 \pi}\cdot \rm sin({\pi}/{2})\hspace{0.15cm}\underline{=0.909},$$
$$F_{x} (r=2) =\rm \frac{1}{2} + \frac{\rm1}{\rm 2} + \rm \frac{1}{2 \pi} \cdot \rm sin(\pi)\hspace{0.15cm}{= 1.000}.$$


(4)  Because of the point symmetry around  $r=0$   resp.  $F_{x} (0) = 1/2$  and because of  $\sin(-x) = -\sin(x)$  this formula holds in the whole domain,  as the following control calculation shows:

$$F_{x} (r=-2) =\rm \frac{1}{2} - \frac{\rm1}{\rm 2} - \rm \frac{1}{2 \pi} \cdot\rm sin(\pi)=0,$$
$$F_{x} (r=-1) =\rm \frac{1}{2} - \frac{\rm1}{\rm 4} - \rm \frac{1}{2 \pi} \cdot\rm sin({\pi}/{2})\hspace{0.15cm}\underline{= 0.091}.$$


(5)  For the probability that  $x$  lies between  $-1$  and  $+1$:

$${\rm Pr}(|\hspace{0.05cm}x\hspace{0.05cm}|< 1)= F_{x}(+1) - F_{ x}(-1)= 0.909-0.091\hspace{0.15cm}\underline{= 0.818}.$$
  • This result agrees exactly with the result of the subtask  (7)  of Exercise 3.1  which was obtained by direct integration üover the WDF.


(6)  The CDF of the discrete valued random variable  $y$  at the location  $y =0$  is the sum of the probabilities of  $-2$,  $-1$  and  $0$.  So:

$$F_y(r = 0)\hspace{0.15cm}\underline{= 0.7}.$$