Cumulative distribution function (what is this 't'?)

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Homework Help Overview

The discussion revolves around understanding the cumulative distribution function (c.d.f.) for a continuous random variable, specifically addressing the role of the variable 't' in its definition. The original poster expresses confusion regarding how to evaluate the c.d.f. for different ranges of 't' based on a given probability density function.

Discussion Character

  • Exploratory, Conceptual clarification, Problem interpretation

Approaches and Questions Raised

  • Participants discuss the definition of the c.d.f. and the significance of 't' as a dummy variable. There are attempts to clarify how to compute the c.d.f. for specified intervals of 't', with some participants suggesting integration of the density function over different ranges.

Discussion Status

The discussion is ongoing, with participants exploring different interpretations of the problem. Some guidance has been provided regarding the need to consider the piecewise nature of the probability density function when calculating the c.d.f. for various cases of 't'.

Contextual Notes

There is an emphasis on understanding the c.d.f. for all values of 't', including those outside the typical range of the random variable. The original poster's homework constraints require evaluating the c.d.f. for specific intervals, which has led to questions about the appropriate approach.

Mattofix
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my question is regarding 'continuous' cumulative distribution functions.

i kind of get it apart from that darn 't' in the definition (see http://upload.wikimedia.org/math/f/2/4/f24252ffb5e5e747b246189b7e1cfcce.png). My textbook, my lecture notes and even wikipedia don't refrer to the 't', apart from in the definition. I wouldn't mind apart from that i am working my way through some questions and have come across quite a few
asking me for the 'c.d.f of X for all t' (for example t<0 and t>2), not asking for the c.d.f of x values (like all of the worked examples i have come across) so what are the questions after?

Here is an example so you understand what my problem is.

Homework Statement


'X is a continuous random quantity with probability density function f(x) = x for 0<x<1, f(x)=2-x for 1 [tex]\leq[/tex] x < 2 with f(x)=0
for all other x. Find the value of Fx(t), the cumulative distribution function of X, for all t (that is t<0 and t>2 as well as 0 [tex]\leq[/tex] t [tex]\leq[/tex] 2 )'


Homework Equations



http://upload.wikimedia.org/math/f/2/4/f24252ffb5e5e747b246189b7e1cfcce.png
http://upload.wikimedia.org/math/f/d/e/fdec25ee8674e78b0bad557daa923a41.png (maybe for when i find the new boundaries they are asking for?)

The Attempt at a Solution


If it was like all of the examples iv seen id say for x<0 F(x)=0, for x>2 F(x)=1, for 0<x<1 F(x)= x[tex]^{2}[/tex]/2 and for 1<x<2 F(x)= 2x - x[tex]^{2}[/tex]/2 , but its not...
 
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If that definition makes any sense to you at all, you must know how to integrate. And if that is true, then you should understand that the t is a "dummy variable"- it does not exist and has no meaning "outside" the integral.

Perhaps it would be easier to understand by looking at the analogous situation in a sum:
[tex]\sum_{n=1}^5 3n- 1= (3(1)-1)+ (3(2)-1)+ (3(3)-1)+ (3(4)-1)+ (3(5)-1)[/tex]
[tex]= 2+ 5+ 8+ 11+ 14= 40[/tex]
the "n" is a "dummy index" which exists only in the sum.
 
ok, but what about the example? i have integrated.

if you can help me get the correct answer for this then hopefully i will be able to make the links and get to grips with it.
 
Mattofix said:

The Attempt at a Solution


for x<0 F(x)=0, for x>2 F(x)=1, for 0<x<1 F(x)= x[tex]^{2}[/tex]/2 and for 1<x<2 F(x)= 2x - x[tex]^{2}[/tex]/2 , but its not...


ok so for t<0 F(t)=0, for t>2 F(t)=1,

and for 0<t<1 F(t)= t[tex]^{2}[/tex]/2 and for 1[tex]\leq[/tex]t<2 F(x)= 2t - t[tex]^{2}[/tex]/2 , but I am not being asked for that, I am being asked for 0[tex]\leq[/tex]t[tex]\leq[/tex]2, what is the answer to this?
 
You are close, but still miss one point:

Since the density is in two "pieces", you need to calculate the distribution function F(t) for two cases.

case 1: 0 < t < 1. Integrate the density from 0 to t to obtain F(t) for this case.

case 2: [tex]1 \le t < 2[/tex]. Here is where you miss something. The correct value for [tex]F(t)[/tex] is found by integrating the density from 0 to t. Since the density is in two pieces, and [tex]t[/tex] is in the second interval, the integral here is broken into two pieces.
Write it out - it is MUCH easier to see in symbols than in my cryptic explanation.
 

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