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

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Hints:
 
Hints:
*The task belongs to the chapter  [[Theory_of_Stochastic_Signals/Cumulative_Distribution_Function|cumulative distribution function]].
+
*The exercise belongs to the chapter  [[Theory_of_Stochastic_Signals/Cumulative_Distribution_Function|cumulative distribution function]].
 
 
 
*Given the following equation:
 
*Given the following equation:
 
:cos2(ax)dx=x2+14asin(2ax).
 
:cos2(ax)dx=x2+14asin(2ax).
The topic of this chapter is illustrated with examples in the (German language) learning video  [[Zusammenhang_zwischen_WDF_und_VTF_(Lernvideo)|Zusammenhang zwischen WDF und VTF]]  relationship between PDF and CDF.
+
*The topic of this chapter is illustrated with examples in the (German language) learning video  [[Zusammenhang_zwischen_WDF_und_VTF_(Lernvideo)|Zusammenhang zwischen WDF und VTF]]  relationship between PDF and CDF.
  
  

Revision as of 21:59, 26 December 2021

Cosine–Square–CDF (top),
Dirac–CDF (bottom)

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  and in the range  2x+2  holds:
fx(x)=1/2cos2(π/4x).
  • Also, the discrete random variable  y  is limited to the range  ±2  Here, the following probabilities apply:
Pr
{\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).
  • The topic of this chapter is illustrated with examples in the (German language) learning video  Zusammenhang zwischen WDF und VTF  \Rightarrow relationship between PDF and CDF.



Questions

1

Which of the following statements are true for the distribution function  F_x(r)  of 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.
Der Verlauf von  F_x(r)  ist monoton steigend.

2

Which of the following statements are true for the distribution function  F_y(r)  of the discrete value 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 here 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  x  is smaller in absolute value than  1 .
Compare the result with the result of the subtask  (7)  of task 3.1.

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

6

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

F_y(r = 0)\ = \


Solution

(1)  Since  x  is a continuous random variable and 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 random variable, the 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 is valid, 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  holds:

{\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 üwhich was obtained by direct integration üover the WDF.


(6)  The VTF of the discrete random sizeö&aerospace;e  y  at the location  y =0  is the sum of the probabilities of  -2-1  and  0,  so holds

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