Difference between revisions of "Aufgaben:Exercise 4.1: Triangular (x, y) Area"

From LNTwww
 
(19 intermediate revisions by 4 users not shown)
Line 1: Line 1:
  
{{quiz-Header|Buchseite=Stochastische Signaltheorie/Zweidimensionale Zufallsgrößen
+
{{quiz-Header|Buchseite=Theory_of_Stochastic_Signals/Two-Dimensional_Random_Variables
 
}}
 
}}
  
[[File:P_ID172__Sto_A_4_1.png|right|Vorgegebenes dreieckigförmiges 2D-Gebiet]]
+
[[File:P_ID172__Sto_A_4_1.png|right|frame|Triangular two-dimensional area]]
Eine 2D-Zufallsgröße ist durch die nebenstehende Skizze definiert. Für ($x$, $y$) können nur Werte innerhalb des durch die drei Eckpunkte (0, 1), (4, 3) und (4, 5) festgelegten dreieckförmigen Gebietes auftreten. Innerhalb des Dreiecks sind alle Zufallsgrößen ($x$, $y$) gleichwahrscheinlich. Für die 2D–WDF gilt somit:
+
A two-dimensional random variable is defined by the adjacent sketch:
 +
*For  $(x, \ y)$  only values within the triangular-shaped region defined by the three vertices  $(0,\ 1)$,$  $(4,\ 3)$,$  and  $(4,\ 5)$  can occur.  
 +
*Within the triangle,  all the random variables  $(x,\ y)$  are equally probable.  
 +
*For the 2D–PDF,  in this domain:
 
:$$f_{xy}(x,y) = A .$$
 
:$$f_{xy}(x,y) = A .$$
  
Zusätzlich ist die Gerade$x = y$  ⇒  „Winkelhalbierende” in obiger Skizze eingezeichnet (siehe Teilaufgabe 2).
+
In addition,  the straight line  $x = y$  ⇒   "angle bisector"  is drawn in the graphic  ⇒  see subtask  '''(2)'''.
  
''Hinweise:''
 
*Die Aufgabe gehört zum  Kapitel [[Stochastische_Signaltheorie/Zweidimensionale_Zufallsgrößen|Zweidimensionale Zufallsgrößen]].
 
*Sollte die Eingabe des Zahlenwertes „0” erforderlich sein, so geben Sie bitte „0.” ein.
 
  
  
===Fragebogen===
+
 
 +
 
 +
 
 +
Hint:
 +
*The exercise belongs to the chapter  [[Theory_of_Stochastic_Signals/Two-Dimensional_Random_Variables|Two-Dimensional Random Variables]].
 +
 +
 
 +
 
 +
===Questions===
  
 
<quiz display=simple>
 
<quiz display=simple>
{Bestimmen Sie die WDF&ndash;Konstante anhand geometrischer &Uuml;berlegungen.
+
{Determine the PDF constant using geometric considerations.
 
|type="{}"}
 
|type="{}"}
$A \ =$ { 0.25 3% }
+
$A \ = \ $ { 0.25 3% }
  
  
{Berechnen Sie die Wahrscheinlichkeit, dass $x$ gr&ouml;&szlig;er als $y$ ist.
+
{Calculate the probability that&nbsp; $x$&nbsp; is greater than&nbsp; $y$.
 
|type="{}"}
 
|type="{}"}
${\rm Pr}(x > y) \ =$ { 0.25 3% }
+
${\rm Pr}(x > y) \ = \ $ { 0.25 3% }
  
  
{Ermitteln Sie die Rand-WDF $f_x(x)$. Berechnen Sie die Wahrscheinlichkeit, dass $x$ gr&ouml;&szlig;er/gleich $2$ ist. &Uuml;berpr&uuml;fen Sie den Wert anhand der 2D&ndash;WDF.
+
{Determine the marginal PDF&nbsp; $f_x(x)$.&nbsp; Calculate the probability that&nbsp; $x$&nbsp; is greater than or equal to&nbsp; $2$. <br>Check the value with the 2D&ndash;PDF.
 
|type="{}"}
 
|type="{}"}
${\rm Pr}(x ≥ 2)\ =$ { 0.75 3% }
+
${\rm Pr}(x ≥ 2)\ = \ $ { 0.75 3% }
  
  
{Ermitteln Sie die Rand-WDF $f_y(y)$. Berechnen Sie die Wahrscheinlichkeit, dass $y$ größer/gleich $3$ ist. Überprüfen Sie den Wert anhand der 2D&ndash;WDF.
+
{Determine the marginal PDF&nbsp; $f_y(y)$.&nbsp; Calculate the probability that&nbsp; $y$&nbsp; is greater than or equal to&nbsp; $3$. <br>Check the value with the 2D&ndash;PDF.
 
|type="{}"}
 
|type="{}"}
${\rm Pr}(y ≥ 3)\ =$ { 0.5 3% }
+
${\rm Pr}(y ≥ 3)\ = \ $ { 0.5 3% }
  
  
{Wie gro&szlig; ist die Wahrscheinlichkeit, dass die Zufallsgr&ouml;&szlig;e $x$ gr&ouml;&szlig;er oder gleich $2$ und gleichzeitig die Zufallsgr&ouml;&szlig;e $y$ gr&ouml;&szlig;er oder gleich $3$ ist?
+
{What is the probability that the random variable&nbsp; $x$&nbsp; is greater than or equal to&nbsp; $2$&nbsp; and at the same time the random variable&nbsp; $y$&nbsp; is greater than or equal to $3$?
 
|type="{}"}
 
|type="{}"}
${\rm Pr}[(x ≥ 2) ∩ (y ≥ 3)]\ =$ { 0.5 3% }
+
${\rm Pr}\big[(x ≥ 2) ∩ (y ≥ 3)\big]\ = \ $ { 0.5 3% }
  
  
{Wie gro&szlig; ist die Wahrscheinlichkeit, dass  $x$ gr&ouml;&szlig;er oder gleich $2$ ist, unter der Bedingung, dass  $y \ge 3$ gilt?
+
{What is the probability that&nbsp; $x$&nbsp; is greater than or equal to&nbsp; $2$&nbsp; given&nbsp; $y \ge 3$?
 
|type="{}"}
 
|type="{}"}
${\rm Pr}[x ≥ 2 | y ≥ 3]\ =$ { 1 3% }
+
${\rm Pr}\big[x ≥ 2\hspace{0.05cm} | \hspace{0.05cm} y ≥ 3\big]\ = \ $ { 1 3% }
  
  
{Wie gro&szlig; ist die Wahrscheinlichkeit, dass  $y \ge 3$ ist, unter der Bedingung, dass $x \ge 2$ gilt?
+
{What is the probability that&nbsp; $y \ge 3$&nbsp; given that&nbsp; $x \ge 2$&nbsp; holds?
 
|type="{}"}
 
|type="{}"}
${\rm Pr}[y ≥ 3 | x ≥ 2]\ =$ { 0.667 3% }
+
${\rm Pr}\big[y ≥ 3\hspace{0.05cm} | \hspace{0.05cm} x ≥ 2\big]\ = \ $ { 0.667 3% }
 
 
 
 
  
 
</quiz>
 
</quiz>
  
===Musterlösung===
+
===Solution===
 
{{ML-Kopf}}
 
{{ML-Kopf}}
:<b>1.</b>&nbsp;&nbsp;Das Volumen unter der zweidimensionalen WDF ist definitionsgem&auml;&szlig; gleich 1:
+
'''(1)'''&nbsp; The volume under the two dimensional PDF is by definition equal to&nbsp; $1$:
 +
[[File:P_ID219__Sto_A_4_1_b.png|right|frame|Triangular 2D&ndash;PDF]]
 
:$$\int_{-\infty}^{+\infty}\int_{-\infty}^{+\infty}f_{xy}(x,y)\, {\rm d}x\, {\rm d}y=1.$$
 
:$$\int_{-\infty}^{+\infty}\int_{-\infty}^{+\infty}f_{xy}(x,y)\, {\rm d}x\, {\rm d}y=1.$$
  
:Die Dreiecksfl&auml;che ist <i>D</i> = 0.5 &middot; 2 &middot; 4 = 4. Da in diesem Definitionsgebiet die WDF konstant gleich <i>A</i> ist, erh&auml;lt man <u><i>A</i> = 1/<i>D</i> = 0.25</u>.
+
*The triangle area is&nbsp; $D = 0.5 \cdot 2 \cdot 4 = 4$.  
[[File:P_ID219__Sto_A_4_1_b.png|right|]]
+
*Since in this definition area the PDF is constantly equal to&nbsp; $A$,&nbsp; we get.
 +
:$$A= 1/D\hspace{0.15cm}\underline{= 0.25}.$$
  
:<b>2.</b>&nbsp;&nbsp;Zur L&ouml;sung gehen wir von nebenstehender Skizze aus. Das Gebiet „<i>x</i> > <i>y</i>“ liegt rechts von der Winkelhalbierenden <i>x</i> = <i>y</i> und ist grün markiert.
 
  
:Die Dreiecksfl&auml;che ist <i>D<sub>b</sub></i> = 0.5 &middot; 1 &middot; 2 = 1, also genau ein Viertel der Gesamtfl&auml;che <i>D</i> des Definitionsgebietes. Daraus folgt <u>Pr(<i>x</i> > <i>y</i>) = 0.25</u>.
+
'''(2)'''&nbsp; For the solution we start from the adjacent sketch.
 +
*The area&nbsp; $x>y$&nbsp; lies to the right of the angle bisector&nbsp; $x=y$&nbsp; and is marked in green.
 +
*This green triangular area is&nbsp; $D_{\rm (2)} = 0.5 \cdot 1 \cdot 2 = 1 $, i.e. exactly one quarter of the total area&nbsp; $D$&nbsp; of the definition area.  
 +
*From this follows&nbsp; ${\rm Pr}(x > y)\hspace{0.15cm}\underline{= 0.25}$.
  
:<b>3.</b>&nbsp;&nbsp;F&uuml;r die gesuchte Rand-WDF gilt in diesem Fall:
+
 
 +
 
 +
'''(3)'''&nbsp; For the wanted marginal PDF holds in this case:
 +
[[File:P_ID220__Sto_A_4_1_c.png|right|frame|Marginal PDF with respect to&nbsp; $x$]]
 
:$$f_x(x)=\int_{-\infty}^{+\infty}f_{xy}(x,y)\, {\rm d}y=A\cdot B_y (x).$$
 
:$$f_x(x)=\int_{-\infty}^{+\infty}f_{xy}(x,y)\, {\rm d}y=A\cdot B_y (x).$$
  
:Hierbei bezeichnet <i>B<sub>y</sub></i>(<i>x</i>) die Breite des Gebietes „<i>f<sub>xy</sub></i> &ne; 0“ in <i>y</i>-Richtung beim betrachteten <i>x</i>-Wert. Es gilt: <i>B<sub>y</sub></i>(<i>x</i>) = <i>x</i>/2. Mit <i>A</i> = 0.25 folgt f&uuml;r 0 &#8804; <i>x</i> &#8804; 4: <i>f<sub>x</sub></i>(<i>x</i>) = <i>x</i>/8.
+
*Here denotes&nbsp; $B_y(x)$&nbsp; the width of the area&nbsp; $f_{xy} \ne 0$&nbsp; in&nbsp; $y$&ndash;direction at the considered&nbsp; $x$&ndash;value.  
[[File:P_ID220__Sto_A_4_1_c.png|left|]]
+
*It holds:&nbsp; $B_y(x) = x/2$.&nbsp; With&nbsp; $A = 0.25$&nbsp; it follows&nbsp; $f_{x}(x) = x/8$&nbsp; for the range&nbsp; $ 0 \le x \le 4$.
:Die gesuchte Wahrscheinlichkeit entspricht der schraffierten Fl&auml;che in nebenstehender Skizze. Man erhält:
 
:$$\rm Pr(\it x\ge \rm 2) = \rm 1-\rm Pr(\it x < \rm 2) \\ = \rm 1-\frac{1}{2}\cdot2\cdot 0.25\hspace{0.15cm}\underline{ =0.75}. $$
 
  
:<br>Zum gleichen Ergebnis gelangt man anhand der 2D-WDF: Rechts von der Senkrechten <i>x</i> = 2 liegt 3/4 des gesamten Definitionsgebiets.
+
*The wanted probability corresponds to the shaded area in the accompanying sketch.&nbsp; One obtains:
[[File:P_ID221__Sto_A_4_1_d.png|right|]]
+
:$$\rm Pr(\it x\ge \rm 2) = \rm 1-\rm Pr(\it x < \rm 2) = \rm 1-\frac{1}{2}\cdot2\cdot 0.25\hspace{0.15cm}\underline{ =0.75}. $$
  
:<b>4.</b>&nbsp;&nbsp;Analog der Musterl&ouml;sung zu (c) gilt:
+
*The same result is obtained using 2D&ndash;PDF:&nbsp; To the right of&nbsp; $x = 2$&nbsp; lies&nbsp; $3/4$&nbsp; of the total definition area.
 +
<br clear=all>
 +
[[File:P_ID221__Sto_A_4_1_d.png|right|frame|Marginal PDF with respect to&nbsp; $y$]]
 +
'''(4)'''&nbsp; Analogous to the solution of the subtask&nbsp; '''(3)'''&nbsp; holds:
 
:$$f_y(y)=\int_{-\infty}^{+\infty}f_{xy}(x,y)\, {\rm d}x=A\cdot B_x (y).$$
 
:$$f_y(y)=\int_{-\infty}^{+\infty}f_{xy}(x,y)\, {\rm d}x=A\cdot B_x (y).$$
  
:Die Ausbreitung des WDF-Gebietes in <i>x</i>-Richtung ist f&uuml;r <i>y</i> &#8804; 1 und <i>y</i> &#8805; 5 jeweils 0. Das Maximum liegt bei <i>y</i> = 3: <i>B<sub>x</sub></i>(<i>y</i> = 3) = 2. Dazwischen ist die Zu&ndash; und Abnahme von <i>B<sub>x</sub></i>(<i>y</i>) linear und es ergibt sich eine dreieckf&ouml;rmige WDF.
+
*The width of PDF area in&nbsp; $x$&ndash;direction is zero for&nbsp; $y \le 1$&nbsp; and&nbsp; $y \ge 5$&nbsp; respectively.  
 +
*The maximum is at&nbsp; $y=3$&nbsp; and gives&nbsp; $B_x(y=3) = 2$.
 +
*In between,&nbsp; the increase&nbsp; and decrease of&nbsp; $B_x(y)$&nbsp; is linear,&nbsp; yielding a triangular-shaped PDF.
 +
*The probability that&nbsp; $y=3$&nbsp; corresponds to the green shaded area in the adjacent sketch.
 +
* Because of the symmetry,&nbsp; one obtains:
 +
:$${\rm Pr}(y ≥ 3)\hspace{0.15cm}\underline{ =0.5}. $$
 +
 
 +
The same result is obtained using 2D&ndash;PDF: &nbsp; Above the horizontal&nbsp; $y= 3$&nbsp; lies half of the total definition area.
 +
 
 +
 
 +
 
 +
[[File:P_ID222__Sto_A_4_1_e.png|right|frame|On subtask '''(5)''']]
 +
'''(5)'''&nbsp; If&nbsp; $y \ge 3$&nbsp; $($red highlighted triangle&nbsp; $D)$,&nbsp; it is always true&nbsp; $x \ge 2$&nbsp; $($green outlined trapezoid&nbsp; $T)$.
 +
*This means:&nbsp; In this example&nbsp; $D$&nbsp; is a subset of&nbsp; $T$,&nbsp; and it holds:
 +
:$${\rm Pr}[(x ≥ 2) ∩ (y ≥ 3)] = {\rm Pr}(y ≥ 3) \hspace{0.15cm}\underline{= 0.50}.$$
 +
 
 +
 
  
:Die Wahrscheinlichkeit, dass <i>y</i> gr&ouml;&szlig;er oder gleich 3 ist, entspricht der grün schraffierten Fl&auml;che und ergibt aufgrund der Symmetrie <u>den Wert 0.5</u>. Zum gleichen Ergebnis kommt man anhand der 2D&ndash;WDF: Oberhalb der Horizontalen <i>y</i> = 3 liegt die H&auml;lfte des gesamten Definitionsgebietes.<br><br>
+
'''(6)'''&nbsp; According to the solution to the subtask&nbsp; '''(5)''',&nbsp; it follows from&nbsp; $y \ge 3$&nbsp; with certainty also&nbsp; $x \ge 2$.  
[[File:P_ID222__Sto_A_4_1_e.png|left|]]
+
*So the conditional probability we are looking for is:
 +
:$${\rm Pr}[x ≥ 2\hspace{0.05cm} | \hspace{0.05cm} y ≥ 3]\hspace{0.15cm}\underline{= 1}.$$
  
:<b>5.</b>&nbsp;&nbsp;Wenn <i>y</i> &#8805; 3 (rot hinterlegtes Dreieck <i>D</i>) ist, gilt stets auch <i>x</i> &#8805; 2 (gr&uuml;n umrandetes Trapez <i>T</i>). Das bedeutet: In diesem Beispiel ist <i>D</i> eine Teilmenge von <i>T</i>, und es gilt:
 
:$$\rm Pr((\it x \ge \rm 2)\cap(\it y \ge \rm 3)) = \rm Pr(\it y \ge \rm 3) \hspace{0.15cm}\underline{= 0.50}.$$
 
  
:<b>6.</b>&nbsp;&nbsp;Entsprechend der L&ouml;sung zur Aufgabe (e) folgt aus „<i>y</i> &#8805; 3“ mit Sicherheit auch „<i>x</i> &#8805; 2“. Somit ist die gesuchte <u>bedingte Wahrscheinlichkeit gleich 1</u>.
 
  
:<b>7.</b>&nbsp;&nbsp;Die Aufgabe kann man z. B. mit dem Satz von Bayes (siehe Kapitel 1.3) und den Ergebnissen aus (2) und (5) und lösen:
+
'''(7)'''&nbsp; This subtask can be solved using Bayes' theorem and the results from&nbsp; '''(2)'''&nbsp; and&nbsp; '''(5)''':
:$$\rm Pr(\it y \ge \rm 3\hspace{0.1cm}|\hspace{0.1cm} \it x \ge \rm 2) = \frac{ \rm Pr((\it x \ge \rm 2)\cap(\it y \ge \rm 3))} {\rm Pr(\it x \ge \rm 2)}\hspace{0.15cm}\underline{=\rm {2}/{3}}.$$
+
:$$\rm Pr(\it y \ge \rm 3\hspace{0.1cm}|\hspace{0.1cm} \it x \ge \rm 2) = \frac{ \rm Pr((\it x \ge \rm 2)\cap(\it y \ge \rm 3))} {\rm Pr(\it x \ge \rm 2)}=2/3\hspace{0.15cm}\underline{=0.667}.$$
  
:Oder anders ausgedr&uuml;ckt: Die Fl&auml;che <i>D</i> des rot hinterlegten Dreiecks macht 2/3 der Fl&auml;che des gr&uuml;n umrandeten Trapezes aus.
+
* Or expressed differently: &nbsp; The area&nbsp; $D$&nbsp; of the triangle with red background makes&nbsp; $2/3$&nbsp; of the area of the trapezoid with green border&nbsp; $T$.
 
{{ML-Fuß}}
 
{{ML-Fuß}}
  
  
  
[[Category:Aufgaben zu Stochastische Signaltheorie|^4.1 Zweidimensionale Zufallsgrößen^]]
+
[[Category:Theory of Stochastic Signals: Exercises|^4.1 Two-Dimensional Random Variables^]]

Latest revision as of 12:05, 7 February 2022

Triangular two-dimensional area

A two-dimensional random variable is defined by the adjacent sketch:

  • For  $(x, \ y)$  only values within the triangular-shaped region defined by the three vertices  $(0,\ 1)$,$  $(4,\ 3)$,$  and  $(4,\ 5)$  can occur.
  • Within the triangle,  all the random variables  $(x,\ y)$  are equally probable.
  • For the 2D–PDF,  in this domain:
$$f_{xy}(x,y) = A .$$

In addition,  the straight line  $x = y$  ⇒   "angle bisector"  is drawn in the graphic  ⇒  see subtask  (2).




Hint:


Questions

1

Determine the PDF constant using geometric considerations.

$A \ = \ $

2

Calculate the probability that  $x$  is greater than  $y$.

${\rm Pr}(x > y) \ = \ $

3

Determine the marginal PDF  $f_x(x)$.  Calculate the probability that  $x$  is greater than or equal to  $2$.
Check the value with the 2D–PDF.

${\rm Pr}(x ≥ 2)\ = \ $

4

Determine the marginal PDF  $f_y(y)$.  Calculate the probability that  $y$  is greater than or equal to  $3$.
Check the value with the 2D–PDF.

${\rm Pr}(y ≥ 3)\ = \ $

5

What is the probability that the random variable  $x$  is greater than or equal to  $2$  and at the same time the random variable  $y$  is greater than or equal to $3$?

${\rm Pr}\big[(x ≥ 2) ∩ (y ≥ 3)\big]\ = \ $

6

What is the probability that  $x$  is greater than or equal to  $2$  given  $y \ge 3$?

${\rm Pr}\big[x ≥ 2\hspace{0.05cm} | \hspace{0.05cm} y ≥ 3\big]\ = \ $

7

What is the probability that  $y \ge 3$  given that  $x \ge 2$  holds?

${\rm Pr}\big[y ≥ 3\hspace{0.05cm} | \hspace{0.05cm} x ≥ 2\big]\ = \ $


Solution

(1)  The volume under the two dimensional PDF is by definition equal to  $1$:

Triangular 2D–PDF
$$\int_{-\infty}^{+\infty}\int_{-\infty}^{+\infty}f_{xy}(x,y)\, {\rm d}x\, {\rm d}y=1.$$
  • The triangle area is  $D = 0.5 \cdot 2 \cdot 4 = 4$.
  • Since in this definition area the PDF is constantly equal to  $A$,  we get.
$$A= 1/D\hspace{0.15cm}\underline{= 0.25}.$$


(2)  For the solution we start from the adjacent sketch.

  • The area  $x>y$  lies to the right of the angle bisector  $x=y$  and is marked in green.
  • This green triangular area is  $D_{\rm (2)} = 0.5 \cdot 1 \cdot 2 = 1 $, i.e. exactly one quarter of the total area  $D$  of the definition area.
  • From this follows  ${\rm Pr}(x > y)\hspace{0.15cm}\underline{= 0.25}$.


(3)  For the wanted marginal PDF holds in this case:

Marginal PDF with respect to  $x$
$$f_x(x)=\int_{-\infty}^{+\infty}f_{xy}(x,y)\, {\rm d}y=A\cdot B_y (x).$$
  • Here denotes  $B_y(x)$  the width of the area  $f_{xy} \ne 0$  in  $y$–direction at the considered  $x$–value.
  • It holds:  $B_y(x) = x/2$.  With  $A = 0.25$  it follows  $f_{x}(x) = x/8$  for the range  $ 0 \le x \le 4$.
  • The wanted probability corresponds to the shaded area in the accompanying sketch.  One obtains:
$$\rm Pr(\it x\ge \rm 2) = \rm 1-\rm Pr(\it x < \rm 2) = \rm 1-\frac{1}{2}\cdot2\cdot 0.25\hspace{0.15cm}\underline{ =0.75}. $$
  • The same result is obtained using 2D–PDF:  To the right of  $x = 2$  lies  $3/4$  of the total definition area.


Marginal PDF with respect to  $y$

(4)  Analogous to the solution of the subtask  (3)  holds:

$$f_y(y)=\int_{-\infty}^{+\infty}f_{xy}(x,y)\, {\rm d}x=A\cdot B_x (y).$$
  • The width of PDF area in  $x$–direction is zero for  $y \le 1$  and  $y \ge 5$  respectively.
  • The maximum is at  $y=3$  and gives  $B_x(y=3) = 2$.
  • In between,  the increase  and decrease of  $B_x(y)$  is linear,  yielding a triangular-shaped PDF.
  • The probability that  $y=3$  corresponds to the green shaded area in the adjacent sketch.
  • Because of the symmetry,  one obtains:
$${\rm Pr}(y ≥ 3)\hspace{0.15cm}\underline{ =0.5}. $$

The same result is obtained using 2D–PDF:   Above the horizontal  $y= 3$  lies half of the total definition area.


On subtask (5)

(5)  If  $y \ge 3$  $($red highlighted triangle  $D)$,  it is always true  $x \ge 2$  $($green outlined trapezoid  $T)$.

  • This means:  In this example  $D$  is a subset of  $T$,  and it holds:
$${\rm Pr}[(x ≥ 2) ∩ (y ≥ 3)] = {\rm Pr}(y ≥ 3) \hspace{0.15cm}\underline{= 0.50}.$$


(6)  According to the solution to the subtask  (5),  it follows from  $y \ge 3$  with certainty also  $x \ge 2$.

  • So the conditional probability we are looking for is:
$${\rm Pr}[x ≥ 2\hspace{0.05cm} | \hspace{0.05cm} y ≥ 3]\hspace{0.15cm}\underline{= 1}.$$


(7)  This subtask can be solved using Bayes' theorem and the results from  (2)  and  (5):

$$\rm Pr(\it y \ge \rm 3\hspace{0.1cm}|\hspace{0.1cm} \it x \ge \rm 2) = \frac{ \rm Pr((\it x \ge \rm 2)\cap(\it y \ge \rm 3))} {\rm Pr(\it x \ge \rm 2)}=2/3\hspace{0.15cm}\underline{=0.667}.$$
  • Or expressed differently:   The area  $D$  of the triangle with red background makes  $2/3$  of the area of the trapezoid with green border  $T$.