Difference between revisions of "Aufgaben:Exercise 4.4Z: Contour Lines of the "2D-PDF""

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{{quiz-Header|Buchseite=Stochastische Signaltheorie/Zweidimensionale Gaußsche Zufallsgrößen
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{{quiz-Header|Buchseite=Theory_of_Stochastic_Signals/Two-Dimensional_Gaussian_Random_Variables
 
}}
 
}}
  
[[File:P_ID297__Sto_Z_4_4.png|right|frame|Gaußsche 2D-WDF:   Höhenlinien]]
+
[[File:EN Sto Z 4 4.png|right|frame|Gaussian 2D–PDF: Contour lines]]
Gegeben ist eine zweidimensionale Gaußsche Zufallsgröße $(x, y)$ mit Mittelwert $(0, 0)$ und der 2D–WDF
+
Given a two-dimensional Gaussian random variable  $(x, y)$  with mean  $(0, 0)$  and the 2D–PDF
:$$f_{xy}(x, y) = C\cdot{\rm e}^{-(x^{\rm 2} + y^{\rm 2} +\sqrt{\rm 2}\hspace{0.05cm}\cdot \hspace{0.05cm} x \hspace{0.05cm}\cdot \hspace{0.05cm} y)}.$$
+
:$$f_{xy}(x,\ y) = C\cdot{\rm e}^{-(x^{\rm 2} + y^{\rm 2} +\sqrt{\rm 2}\hspace{0.05cm}\cdot \hspace{0.05cm} x \hspace{0.05cm}\cdot \hspace{0.05cm} y)}.$$
  
Bekannt ist weiter, dass die beiden Streuungen $\sigma_x$ und $\sigma_y$ jeweils gleich $1$ sind. In der Skizze eingetragen sind:
+
It is further known that the standard deviations are  $\sigma_x=\sigma_y=1.$ 
* Eine Höhenlinie dieser WDF für $f_{xy}(x,y) =0.2$,
 
* die Ellipsenhauptachse $\rm (EA)$, und
 
* die Korrelationsgerade $y=K(x)$.
 
  
 +
Entered in the sketch are:
 +
* a contour line of this PDF for  $f_{xy}(x,y) =0.2$,
 +
* the  (dark blue)  ellipse major axis  $\rm (EA)$,  and
 +
* the  (red)  "correlation line"  or  "regression line" $\rm (RL)$.
  
  
  
''Hinweise:''
 
*Die Aufgabe gehört zum  Kapitel [[Stochastische_Signaltheorie/Zweidimensionale_Zufallsgrößen|Zweidimensionale Zufallsgrößen]].
 
  
*Weitere Informationen zu dieser Thematik liefert das Lernvideo [[Gaußsche_2D-Zufallsgrößen_(Lernvideo)|Gaußsche 2D-Zufallsgrößen]]:
 
::Teil 1:   Gaußsche Zufallsgrößen ohne statistische Bindungen, 
 
::Teil 2:   Gaußsche Zufallsgrößen mit statistischen Bindungen.
 
 
  
  
  
 +
Hints:
 +
*The exercise belongs to the chapter  [[Theory_of_Stochastic_Signals/Two-Dimensional_Gaussian_Random_Variables|Two-dimensional Gaussian Random Variables]].
 +
*More information on this topic is provided in the  (German language) learning video  [[Gaußsche_2D-Zufallsgrößen_(Lernvideo)|"Gaußsche 2D-Zufallsgrößen"]]:
 +
::Part 1:   Gaussian random variables without statistical bindings, 
 +
::Part 2:   Gaussian random variables with statistical bindings.
  
===Fragebogen===
+
 
 +
===Questions===
  
 
<quiz display=simple>
 
<quiz display=simple>
{Wie gro&szlig; ist der Korrelationskoeffizient $\rho_{xy}$?
+
{What is the correlation coefficient&nbsp; $\rho_{xy}$?
 
|type="{}"}
 
|type="{}"}
 
$\rho_{xy} \ = \ $ { -0.727--0.687 }
 
$\rho_{xy} \ = \ $ { -0.727--0.687 }
  
  
{Wie gro&szlig; ist der Maximalwert $C = f_{xy}(0, 0)$ der WDF?
+
{What is the maximum PDF value&nbsp; $C = f_{xy}(0, 0)$?
 
|type="{}"}
 
|type="{}"}
 
$C \ = \ $ { 0.225 3% }
 
$C \ = \ $ { 0.225 3% }
  
  
{Wie groß ist der Winkel $\alpha$ zwischen Ellipsenhauptachse $\rm (EA)$ und $x$&ndash;Achse?
+
{What is the angle&nbsp; $\alpha$&nbsp; between ellipse major axis&nbsp; $\rm (EA)$&nbsp; and&nbsp; $x$&ndash;axis?
 
|type="{}"}
 
|type="{}"}
$\alpha\ = \ $ { -46--44 } $ \ \rm Grad$
+
$\alpha\ = \ $ { -46--44 } $ \ \rm degrees$
  
  
{Bei welchen Werten $x_0$ bzw. $y_0$ schneidet die H&ouml;henlinie $f_{xy}(x,y) = 0.2$ die Ellipsenhauptachse?  
+
{At what values&nbsp; $x_0$&nbsp; and&nbsp; $y_0$&nbsp; does the contour line&nbsp; $f_{xy}(x,y) = 0.2$&nbsp; intersect the ellipse major axis?&nbsp; What is the relationship between&nbsp; $x_0$&nbsp; and&nbsp; $y_0$?
<br>Welcher Zusammenhang besteht zwischen $x_0$ und $y_0$?
 
 
|type="{}"}
 
|type="{}"}
 
$x_0/y_0 \ = \ $ { -1.03--0.97 }
 
$x_0/y_0 \ = \ $ { -1.03--0.97 }
  
  
{Welche Aussagen treffen hinsichtlich der Korrelationsgeraden $K(x)$ zu?
+
{Which statements are true regarding the correlation line&nbsp; $y=K\cdot x$&nbsp;?
 
|type="[]"}
 
|type="[]"}
- Die Korrelationsgerade ist steiler als die Ellipsenhauptachse.
+
- The correlation line is steeper than the ellipse major axis.
+ Der Winkel von $K(x)$ gegen&uuml;ber der $x$&ndash;Achse ist etwa $-35^\circ$.
+
+ The angle ofthe correlation line with respect to the&nbsp; $x$&ndash;axis is about&nbsp; $-35^\circ$.
+ Die Korrelationsgerade schneidet alle H&ouml;henlinien dort, wo an die Ellipse eine vertikale Tangente angelegt werden kann.
+
+ The correlation line intersects all contour line where a vertical tangent can be applied to the ellipse.
  
  
 
</quiz>
 
</quiz>
  
===Musterlösung===
+
===Solution===
 
{{ML-Kopf}}
 
{{ML-Kopf}}
'''(1)'''&nbsp; Auch ohne die Angabe $\sigma_x = \sigma_y = 1$ könnte man erkennen, dass die beiden Streuungen gleich sind, da im Exponenten der 2D&ndash;WDF $f_{xy}(x, y)$ die Koeffizienten bei $x^2$ und $y^2$ gleich sind. Durch Koeffizientenvergleich erhält man somit:
+
'''(1)'''&nbsp; Even without specifying&nbsp; $\sigma_x = \sigma_y = 1$&nbsp; one could see that the standard deviations&nbsp; $\sigma_x$&nbsp; and&nbsp; $\sigma_y$&nbsp; are equal,&nbsp; <br>since in the exponent of $f_{xy}(x, y)$&nbsp; the coefficients at&nbsp; $x^2$&nbsp; and&nbsp; $y^2$&nbsp; are equal.  
 +
*By comparing coefficients,&nbsp; we thus obtain:
 
:$$\frac{- 2 \rho_{xy}}{\sigma_x\cdot\sigma_y} = \sqrt{2}\hspace{0.3cm}\Rightarrow\hspace{0.3cm}
 
:$$\frac{- 2 \rho_{xy}}{\sigma_x\cdot\sigma_y} = \sqrt{2}\hspace{0.3cm}\Rightarrow\hspace{0.3cm}
 
\rho_{xy}=\frac{-1}{\sqrt{2}} \hspace{0.15cm}\underline{\approx -0.707}.$$
 
\rho_{xy}=\frac{-1}{\sqrt{2}} \hspace{0.15cm}\underline{\approx -0.707}.$$
  
'''(2)'''&nbsp; Mit den unter Punkt (1) berechneten Zahlenwerten erhalten wir:
+
 
 +
'''(2)'''&nbsp; Using the numerical values calculated in point&nbsp; '''(1)''',&nbsp; we obtain:
 
:$$C=\frac{\rm 1}{\rm 2\it\pi\cdot\sigma_x\cdot\sigma_y\cdot\sqrt{\rm 1 - \rho_{xy}^{\rm 2}}}
 
:$$C=\frac{\rm 1}{\rm 2\it\pi\cdot\sigma_x\cdot\sigma_y\cdot\sqrt{\rm 1 - \rho_{xy}^{\rm 2}}}
 
=\frac{\rm 1}{\rm 2\pi\cdot\rm 1\cdot 1\cdot\sqrt{0.5}}=\frac{\rm 1}{\sqrt{\rm 2}\cdot \pi}\hspace{0.15cm}\underline{\approx \rm 0.225}.$$
 
=\frac{\rm 1}{\rm 2\pi\cdot\rm 1\cdot 1\cdot\sqrt{0.5}}=\frac{\rm 1}{\sqrt{\rm 2}\cdot \pi}\hspace{0.15cm}\underline{\approx \rm 0.225}.$$
  
'''(3)'''&nbsp; Die allgemeine Gleichung lautet:
 
:$$\alpha = {\rm 1}/{\rm 2}\cdot \rm arctan(\rm 2 \cdot\it \rho_{xy}\cdot \frac{\sigma_x\cdot\sigma_y}{\sigma_x^{\rm 2} - \sigma_y^{\rm 2}}).$$
 
  
Gilt $\sigma_x = \sigma_y$ und $\rho_{xy} \ne 0$, so ist der Winkel immer $\alpha = \pm 45^\circ$, wobei das Vorzeichen gleich dem Vorzeichen von $\rho_{xy}$ ist. Im vorliegenden Fall gilt $\alpha\hspace{0.15cm}\underline{ = -45^\circ}$.
+
'''(3)'''&nbsp; The general equation is:
 +
:$$\alpha = {\rm 1}/{\rm 2}\cdot \rm arctan \ (\rm 2 \cdot\it \rho_{xy}\cdot \frac{\sigma_x\cdot\sigma_y}{\sigma_x^{\rm 2} - \sigma_y^{\rm 2}}{\rm ).}$$
 +
 
 +
*Applies&nbsp; $\sigma_x = \sigma_y$&nbsp; and&nbsp; $\rho_{xy} \ne 0$,&nbsp; then the angle is always&nbsp; $\alpha = \pm 45^\circ$,&nbsp; where the sign is equal to the sign of&nbsp; $\rho_{xy}$.  
 +
*In the present case&nbsp; $\alpha\hspace{0.15cm}\underline{ = -45^\circ}$ holds.
 +
 
 +
 
  
'''(4)'''&nbsp; F&uuml;r die eingezeichnete H&ouml;henlinie gilt:
+
'''(4)'''&nbsp; For the plotted contour line holds:
:$$f_{xy}(x, y)=\frac{\rm 1}{\sqrt{\rm 2}\cdot \pi}\cdot {\rm e}^{(\it x^{\rm 2} + y^{\rm 2} + \sqrt{\rm 2}\hspace{0.05cm}\cdot \hspace{0.05cm} x \hspace{0.05cm}\cdot \hspace{0.05cm}y)}=\rm 0.2$$
+
:$$f_{xy}(x, y)=\frac{1}{\sqrt{2}\cdot \pi}\cdot {\rm e}^{(x^{2} + y^{2} + \sqrt{2}\hspace{0.05cm}\cdot \hspace{0.05cm} x \hspace{0.05cm}\cdot \hspace{0.05cm}y)}=0.2\hspace{0.3cm}
:$$\Rightarrow {\rm e}^{-( x^{\rm 2} + y^{\rm 2} + \sqrt{\rm 2}\hspace{0.05cm} \cdot \hspace{0.05cm} x \hspace{0.05cm} \cdot \hspace{0.05cm}y)} = 0.8885
+
\Rightarrow \hspace{0.3cm}{\rm e}^{-(x^{2} + y^{2} + \sqrt{2}\hspace{0.05cm} \cdot \hspace{0.05cm} x \hspace{0.05cm} \cdot \hspace{0.05cm}y)} = 0.8885
\hspace{0.5cm}\Rightarrow \hspace{0.5cm} x^{\rm 2} + y^{\rm 2} + \sqrt{\rm 2}\cdot\hspace{0.05cm} x \hspace{0.05cm} \cdot \hspace{0.05cm}y = -{\rm ln(0.8885)} \approx\rm 0.118.$$
+
\hspace{0.5cm}\Rightarrow \hspace{0.5cm} x^{\rm 2} + y^{\rm 2} + \sqrt{\rm 2}\cdot\hspace{0.05cm} x \hspace{0.05cm} \cdot \hspace{0.05cm}y = -{\rm ln(0.8885)} \approx\rm 0.118.$$
  
Der Winkel der Ellipsenhauptachse ist $\alpha{ = -45^\circ}$. Deshalb muss $y_0 = - x_0$ gelten. Daraus folgt weiter:
+
*The angle of the ellipse major axis is&nbsp; $\alpha = -45^\circ$.&nbsp; Therefore&nbsp; $y_0 = - x_0$&nbsp; must hold.&nbsp; It further follows:
 
:$$x_{\rm 0}^{\rm 2} + (-x_{\rm 0})^{\rm 2} + \sqrt{\rm 2}\cdot x_{\rm 0}(-x_{\rm 0}) = 0.118$$
 
:$$x_{\rm 0}^{\rm 2} + (-x_{\rm 0})^{\rm 2} + \sqrt{\rm 2}\cdot x_{\rm 0}(-x_{\rm 0}) = 0.118$$
:$$\Rightarrow (\rm 2 - \sqrt{\rm 2})\cdot \it x_{\rm 0}^{\rm 2} = {\rm 0.118}  
+
:$$\Rightarrow \hspace{0.3cm}(\rm 2 - \sqrt{\rm 2})\cdot \it x_{\rm 0}^{\rm 2} = {\rm 0.118}  
\hspace{0.5cm}\Rightarrow \hspace{0.5cm} x_{\rm 0}^{\rm 2} \approx \frac{\rm0.118}{\rm0.585}\approx\rm 0.202; \hspace{0.5cm} {\it x}_{\rm 0}\approx\pm\rm 0.450.$$
+
\hspace{0.5cm}\rightarrow \hspace{0.5cm} x_{\rm 0}^{\rm 2} \approx \frac{\rm0.118}{\rm0.585}\approx\rm 0.202; \hspace{0.5cm} {\it x}_{\rm 0}\approx\pm\rm 0.450.$$
 +
 
 +
*The two intersections of the plotted contour lines with the ellipse major axis are thus at&nbsp; $(+0.45, -0.45)$&nbsp; and&nbsp; $(-0.45, +0.45)$.
 +
*The quotient in both cases is&nbsp; $x_0/y_0 \hspace{0.15cm}\underline{ = -1}$.
 +
 
 +
 
 +
 
 +
 
 +
'''(5)'''&nbsp; Correct are&nbsp; <u>the proposed solutions 2 and 3</u>:
 +
*With&nbsp; $\sigma_x = \sigma_y$&nbsp; and the result of the subtask&nbsp; '''(1)'''&nbsp; holds for the angle of the correlation line:
 +
:$$\theta_{y\hspace{0.05cm}\rightarrow \hspace{0.05cm}x} = \arctan (\rho_{\it xy})=\arctan(-{\rm 1}/{\sqrt{\rm 2}})\approx -\rm 35.3^{\circ}.$$
 +
*This means: &nbsp; The first statement is false and the second is true.
  
Die beiden Schnittpunkte der eingezeichneten H&ouml;henlinien mit der Ellipsenhauptachse liegen somit bei $(+0.45, -0.45)$ und $(-0.45, +0.45)$. Der Quotient ist in beiden Fällen  $x_0/y_0 \hspace{0.15cm}\underline{ = -1}$.
 
  
 +
The following is the&nbsp; <u>proof of the correctness of the last statement</u>:
 +
*Solving the elliptic equation&nbsp; $($with&nbsp; $z = 0. 118)$,&nbsp; so&nbsp;
 +
:$$x^{\rm 2}+ y^{\rm 2} +\sqrt{\rm 2}\cdot \it x\cdot \it y - \it z = \rm 0.$$
  
'''(5)'''&nbsp; Richtig sind <u>die Lösungsvorschläge 2 und 3</u>:
+
After solving the quadratic equation:
*Mit $\sigma_x = \sigma_y$ und dem Ergebnis der Teilaufgabe (1) gilt f&uuml;r den Winkel der Korrelationsgeraden:
+
:$$y_{\rm 1, \ 2}={\sqrt{\rm 2}}/ {\rm 2} \cdot x\pm\sqrt{{x^{\rm 2}}/{\rm 2}-x^{\rm 2}+{\it z}}
:$$\theta_{y\rightarrow x} = \arctan (\rho_{\it xy})=\arctan(-{\rm 1}/{\sqrt{\rm 2}})\approx -\rm 35.3^{\circ}.$$
+
\hspace{0.5cm}\Rightarrow \hspace{0.5cm} y_{\rm 1, \ 2}={\it x}/{\sqrt{\rm 2}}\pm \sqrt{z-{x^{\rm 2}}/{\rm 2}}.$$
:Das bedeutet: Die erste Aussage ist falsch und die zweite richtig.
+
*The vertical tangent results for the case that the two solutions&nbsp; $y_{\rm 1,\ \rm 2}$&nbsp; are identical.&nbsp; That is: &nbsp; The root expression must result in zero.
*Nachfolgend der Beweis für die Richtigkeit der letzten Aussage: L&ouml;st man die Ellipsengleichung (mit $z = 0.118$), also $x^{\rm 2}+ y^{\rm 2} +\sqrt{\rm 2}\cdot \it x\cdot \it y - \it z = \rm 0 ,$ nach $y$ auf, so erh&auml;lt man nach L&ouml;sung einer quadratischen Gleichung
+
*The solution for positive&nbsp; $x$&nbsp; is then: &nbsp; $x_{\rm T}=\sqrt{\rm 2\cdot \it z}=\rm \rm 0.485.$
:$$y_{\rm 1, \ 2}={\sqrt{\rm 2}}/ {\rm 2} \cdot x\pm\sqrt{{x^{\rm 2}}/{\rm 2}-x^{\rm 2}+{\it z}}
+
*Inserted into the ellipse equation one obtains for the&nbsp; $y$&ndash;value of the tangent point:  
\hspace{0.5cm}\Rightarrow \hspace{0.5cm} y_{\rm 1, \ 2}={\it x}/{\sqrt{\rm 2}}\pm \sqrt{z-{x^{\rm 2}}/{\rm 2}}.$$
 
*Die vertikale Tangente ergibt sich f&uuml;r den Fall, dass die beiden L&ouml;sungen $y_{\rm 1, \ 2}$ identisch sind. Das heißt: der Wurzelausdruck muss den Wert $0$ ergeben. Die L&ouml;sung f&uuml;r positives $x$ lautet dann: &nbsp; $x_{\rm T}=\sqrt{\rm 2\cdot \it z}=\rm \rm 0.485.$
 
*Eingesetzt in die Ellipsengleichung erh&auml;lt man f&uuml;r den $y$-Wert des Tangentialpunktes:  
 
 
:$$x_{\rm T}^{\rm 2} + y_{\rm T}^{\rm 2} + \sqrt{2} \cdot x_{\rm T} \cdot y_{\rm T} - z = 0
 
:$$x_{\rm T}^{\rm 2} + y_{\rm T}^{\rm 2} + \sqrt{2} \cdot x_{\rm T} \cdot y_{\rm T} - z = 0
\hspace{0.5cm}\Rightarrow \hspace{0.5cm} 2 z + y_{\rm T}^{\rm 2} + 2\sqrt{ z}\cdot y_{\rm T} - z = 0$$
+
\hspace{0.5cm}\Rightarrow \hspace{0.5cm} 2 z + y_{\rm T}^{\rm 2} + 2\sqrt{ z}\cdot y_{\rm T} - z = 0$$
:$$\Rightarrow y_{\rm T}^{\rm 2} + 2\sqrt{ z}\cdot y_{\rm T} + z = 0
+
:$$\Rightarrow \hspace{0.3cm}y_{\rm T}^{\rm 2} + 2\sqrt{ z}\cdot y_{\rm T} + z = 0
\hspace{0.5cm}\Rightarrow \hspace{0.5cm} (y_{\rm T} + \sqrt{ z}) = 0\hspace{0.5cm}\Rightarrow \hspace{0.5cm} y_{\rm T} = -\sqrt{ z} = -0.343.$$
+
\hspace{0.5cm}\Rightarrow \hspace{0.5cm} (y_{\rm T} + \sqrt{ z}) = 0\hspace{0.5cm}\Rightarrow \hspace{0.5cm} y_{\rm T} = -\sqrt{ z} = -0.343.$$
  
*Daraus ergibt sich $y_{\rm T}=-{x_{\rm T}}/{\sqrt{\rm 2}}.$ Das bedeutet aber auch: Der Tangentialpunkt $(x_{\rm T}, y_{\rm T})$ liegt exakt auf der Korrelationsgeraden  $y=K(x)=-{ x}/{\sqrt{\rm 2}}.$
+
*This gives&nbsp; $y_{\rm T}=-{x_{\rm T}}/{\sqrt{\rm 2}}. $&nbsp; But this also means: &nbsp; The tangent point&nbsp; $(x_{\rm T}, y_{\rm T})$&nbsp; lies exactly on the correlation line&nbsp; $y=K(x)=-{ x}/{\sqrt{\rm 2}}.$
  
 
{{ML-Fuß}}
 
{{ML-Fuß}}
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[[Category:Aufgaben zu Stochastische Signaltheorie|^4.2 Gaußsche 2D-Zufallsgrößen^]]
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[[Category:Theory of Stochastic Signals: Exercises|^4.2 Gaussian 2D Random Variables^]]

Latest revision as of 16:43, 10 April 2022

Gaussian 2D–PDF: Contour lines

Given a two-dimensional Gaussian random variable  $(x, y)$  with mean  $(0, 0)$  and the 2D–PDF

$$f_{xy}(x,\ y) = C\cdot{\rm e}^{-(x^{\rm 2} + y^{\rm 2} +\sqrt{\rm 2}\hspace{0.05cm}\cdot \hspace{0.05cm} x \hspace{0.05cm}\cdot \hspace{0.05cm} y)}.$$

It is further known that the standard deviations are  $\sigma_x=\sigma_y=1.$ 

Entered in the sketch are:

  • a contour line of this PDF for  $f_{xy}(x,y) =0.2$,
  • the  (dark blue)  ellipse major axis  $\rm (EA)$,  and
  • the  (red)  "correlation line"  or  "regression line" $\rm (RL)$.




Hints:

Part 1:   Gaussian random variables without statistical bindings,
Part 2:   Gaussian random variables with statistical bindings.


Questions

1

What is the correlation coefficient  $\rho_{xy}$?

$\rho_{xy} \ = \ $

2

What is the maximum PDF value  $C = f_{xy}(0, 0)$?

$C \ = \ $

3

What is the angle  $\alpha$  between ellipse major axis  $\rm (EA)$  and  $x$–axis?

$\alpha\ = \ $

$ \ \rm degrees$

4

At what values  $x_0$  and  $y_0$  does the contour line  $f_{xy}(x,y) = 0.2$  intersect the ellipse major axis?  What is the relationship between  $x_0$  and  $y_0$?

$x_0/y_0 \ = \ $

5

Which statements are true regarding the correlation line  $y=K\cdot x$ ?

The correlation line is steeper than the ellipse major axis.
The angle ofthe correlation line with respect to the  $x$–axis is about  $-35^\circ$.
The correlation line intersects all contour line where a vertical tangent can be applied to the ellipse.


Solution

(1)  Even without specifying  $\sigma_x = \sigma_y = 1$  one could see that the standard deviations  $\sigma_x$  and  $\sigma_y$  are equal, 
since in the exponent of $f_{xy}(x, y)$  the coefficients at  $x^2$  and  $y^2$  are equal.

  • By comparing coefficients,  we thus obtain:
$$\frac{- 2 \rho_{xy}}{\sigma_x\cdot\sigma_y} = \sqrt{2}\hspace{0.3cm}\Rightarrow\hspace{0.3cm} \rho_{xy}=\frac{-1}{\sqrt{2}} \hspace{0.15cm}\underline{\approx -0.707}.$$


(2)  Using the numerical values calculated in point  (1),  we obtain:

$$C=\frac{\rm 1}{\rm 2\it\pi\cdot\sigma_x\cdot\sigma_y\cdot\sqrt{\rm 1 - \rho_{xy}^{\rm 2}}} =\frac{\rm 1}{\rm 2\pi\cdot\rm 1\cdot 1\cdot\sqrt{0.5}}=\frac{\rm 1}{\sqrt{\rm 2}\cdot \pi}\hspace{0.15cm}\underline{\approx \rm 0.225}.$$


(3)  The general equation is:

$$\alpha = {\rm 1}/{\rm 2}\cdot \rm arctan \ (\rm 2 \cdot\it \rho_{xy}\cdot \frac{\sigma_x\cdot\sigma_y}{\sigma_x^{\rm 2} - \sigma_y^{\rm 2}}{\rm ).}$$
  • Applies  $\sigma_x = \sigma_y$  and  $\rho_{xy} \ne 0$,  then the angle is always  $\alpha = \pm 45^\circ$,  where the sign is equal to the sign of  $\rho_{xy}$.
  • In the present case  $\alpha\hspace{0.15cm}\underline{ = -45^\circ}$ holds.


(4)  For the plotted contour line holds:

$$f_{xy}(x, y)=\frac{1}{\sqrt{2}\cdot \pi}\cdot {\rm e}^{(x^{2} + y^{2} + \sqrt{2}\hspace{0.05cm}\cdot \hspace{0.05cm} x \hspace{0.05cm}\cdot \hspace{0.05cm}y)}=0.2\hspace{0.3cm} \Rightarrow \hspace{0.3cm}{\rm e}^{-(x^{2} + y^{2} + \sqrt{2}\hspace{0.05cm} \cdot \hspace{0.05cm} x \hspace{0.05cm} \cdot \hspace{0.05cm}y)} = 0.8885 \hspace{0.5cm}\Rightarrow \hspace{0.5cm} x^{\rm 2} + y^{\rm 2} + \sqrt{\rm 2}\cdot\hspace{0.05cm} x \hspace{0.05cm} \cdot \hspace{0.05cm}y = -{\rm ln(0.8885)} \approx\rm 0.118.$$
  • The angle of the ellipse major axis is  $\alpha = -45^\circ$.  Therefore  $y_0 = - x_0$  must hold.  It further follows:
$$x_{\rm 0}^{\rm 2} + (-x_{\rm 0})^{\rm 2} + \sqrt{\rm 2}\cdot x_{\rm 0}(-x_{\rm 0}) = 0.118$$
$$\Rightarrow \hspace{0.3cm}(\rm 2 - \sqrt{\rm 2})\cdot \it x_{\rm 0}^{\rm 2} = {\rm 0.118} \hspace{0.5cm}\rightarrow \hspace{0.5cm} x_{\rm 0}^{\rm 2} \approx \frac{\rm0.118}{\rm0.585}\approx\rm 0.202; \hspace{0.5cm} {\it x}_{\rm 0}\approx\pm\rm 0.450.$$
  • The two intersections of the plotted contour lines with the ellipse major axis are thus at  $(+0.45, -0.45)$  and  $(-0.45, +0.45)$.
  • The quotient in both cases is  $x_0/y_0 \hspace{0.15cm}\underline{ = -1}$.



(5)  Correct are  the proposed solutions 2 and 3:

  • With  $\sigma_x = \sigma_y$  and the result of the subtask  (1)  holds for the angle of the correlation line:
$$\theta_{y\hspace{0.05cm}\rightarrow \hspace{0.05cm}x} = \arctan (\rho_{\it xy})=\arctan(-{\rm 1}/{\sqrt{\rm 2}})\approx -\rm 35.3^{\circ}.$$
  • This means:   The first statement is false and the second is true.


The following is the  proof of the correctness of the last statement:

  • Solving the elliptic equation  $($with  $z = 0. 118)$,  so 
$$x^{\rm 2}+ y^{\rm 2} +\sqrt{\rm 2}\cdot \it x\cdot \it y - \it z = \rm 0.$$

After solving the quadratic equation:

$$y_{\rm 1, \ 2}={\sqrt{\rm 2}}/ {\rm 2} \cdot x\pm\sqrt{{x^{\rm 2}}/{\rm 2}-x^{\rm 2}+{\it z}} \hspace{0.5cm}\Rightarrow \hspace{0.5cm} y_{\rm 1, \ 2}={\it x}/{\sqrt{\rm 2}}\pm \sqrt{z-{x^{\rm 2}}/{\rm 2}}.$$
  • The vertical tangent results for the case that the two solutions  $y_{\rm 1,\ \rm 2}$  are identical.  That is:   The root expression must result in zero.
  • The solution for positive  $x$  is then:   $x_{\rm T}=\sqrt{\rm 2\cdot \it z}=\rm \rm 0.485.$
  • Inserted into the ellipse equation one obtains for the  $y$–value of the tangent point:
$$x_{\rm T}^{\rm 2} + y_{\rm T}^{\rm 2} + \sqrt{2} \cdot x_{\rm T} \cdot y_{\rm T} - z = 0 \hspace{0.5cm}\Rightarrow \hspace{0.5cm} 2 z + y_{\rm T}^{\rm 2} + 2\sqrt{ z}\cdot y_{\rm T} - z = 0$$
$$\Rightarrow \hspace{0.3cm}y_{\rm T}^{\rm 2} + 2\sqrt{ z}\cdot y_{\rm T} + z = 0 \hspace{0.5cm}\Rightarrow \hspace{0.5cm} (y_{\rm T} + \sqrt{ z}) = 0\hspace{0.5cm}\Rightarrow \hspace{0.5cm} y_{\rm T} = -\sqrt{ z} = -0.343.$$
  • This gives  $y_{\rm T}=-{x_{\rm T}}/{\sqrt{\rm 2}}. $  But this also means:   The tangent point  $(x_{\rm T}, y_{\rm T})$  lies exactly on the correlation line  $y=K(x)=-{ x}/{\sqrt{\rm 2}}.$