Finding CDF for Continuous RVs problem

In summary: So, if you are integrating from a lower value to a higher value, you will be accumulating more area than if you were integrating from a higher value to a lower value.
  • #1
nontradstuden
54
0

Homework Statement


I'm given the pdf and asked to find F(y)/ cdf. I've calculated it many times, but I'm not getting the right numbers. the pdf is

f(y)= .5, ....-2≤y≤0
.75-.25y,...1≤y≤3
0,...elsewhere

so that means

f(y)= 0,...y< -2
0.5, ...-2≤y≤0
0,...0<y<1
.75-.25y,...1≤y≤3
0,... y>3

right?

So, my CDF is

F(y)= c1,...... y<-2
.5y +c2,..... -2≤y≤0
c3, .......0<y<1
.75y- .125y^2+ c4,... 1≤y≤3
c5,.........y>3

so, I found the constants, but I'm not getting c5=1.

0=c1=.5y+c2 at y=-2
so 1=c2.5y+1=c3 at y=0
so 1=c31=c3=.75y- .125y^2+ c4 at y=1
1= .75- .125+ c4
1-.625= .375=c4.75y-.125y^2+ .375= c5 at y=3
.75*3 -.125(9) +.375= c5
2.25 - 1.125 + .375= 1.5=c5≠1I don't know where I'm going wrong. Could you show me?? -_- Much thanks.I hope this is legible...
 
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  • #2
Assuming you've given the right problem statement, I think the question is just flawed. Take a step back from calculus for a bit and consider you are just accumulating area. The function is zero before y = -2, so at that point the accumulation is zero. You then accumulate a rectangle of length 2 (from -2 to 0) and height .5. The area accumulated it 2*.5 = 1. You've already gotten 1 area... so the fact you will be accumulating more is a problem.
 
  • #3
@RoshanBBQ,

Yeah, I looked at it from a geometric pov and it came out to be more than 1, but I've worked this problem many times, with a calculator and without... being careful with the numbers and such... I've just e-mailed my professor, so we shall see D:... Thanks for your quick response!
 
  • #4
nontradstuden said:

Homework Statement


I'm given the pdf and asked to find F(y)/ cdf. I've calculated it many times, but I'm not getting the right numbers. the pdf is

f(y)= .5, ....-2≤y≤0
.75-.25y,...1≤y≤3
0,...elsewhere

so that means

f(y)= 0,...y< -2
0.5, ...-2≤y≤0
0,...0<y<1
.75-.25y,...1≤y≤3
0,... y>3

right?

So, my CDF is

F(y)= c1,...... y<-2
.5y +c2,..... -2≤y≤0
c3, .......0<y<1
.75y- .125y^2+ c4,... 1≤y≤3
c5,.........y>3

so, I found the constants, but I'm not getting c5=1.

0=c1=.5y+c2 at y=-2
so 1=c2


.5y+1=c3 at y=0
so 1=c3


1=c3=.75y- .125y^2+ c4 at y=1
1= .75- .125+ c4
1-.625= .375=c4


.75y-.125y^2+ .375= c5 at y=3
.75*3 -.125(9) +.375= c5
2.25 - 1.125 + .375= 1.5=c5≠1


I don't know where I'm going wrong. Could you show me?? -_- Much thanks.


I hope this is legible...

For any z > -2 the CDF is [itex]F(z) = \int_{-2}^z f(y) \, dy,[/itex] so there is no need to introduce arbitrary constants of integration. However, your f(y) integrates to 3/2 > 1, so is not a legitimate probability density function.

RGV
 

FAQ: Finding CDF for Continuous RVs problem

1. What is a Continuous Random Variable (CRV)?

A Continuous Random Variable (CRV) is a type of random variable that can take on any numerical value within a certain range or interval. Unlike a discrete random variable, which can only take on specific, separate values, a CRV can take on any value within a continuous range. Examples of CRVs include height, weight, and time.

2. Why is it important to find the CDF for Continuous RVs?

The Cumulative Distribution Function (CDF) for Continuous RVs gives the probability that a CRV will take on a value less than or equal to a given value. This information is important for understanding the behavior and characteristics of the CRV, as well as for making predictions and calculations based on the CRV.

3. How do you find the CDF for Continuous RVs?

The CDF for a Continuous RV can be found by integrating the Probability Density Function (PDF) of the CRV over a given range. The resulting function will give the cumulative probability for each value within that range. Alternatively, the CDF can also be found by using a table or graph of the PDF and calculating the area under the curve up to a certain value.

4. What is the difference between the PDF and CDF for Continuous RVs?

The Probability Density Function (PDF) gives the probability that a CRV will take on a specific value, while the Cumulative Distribution Function (CDF) gives the probability that the CRV will take on a value less than or equal to a given value. In other words, the PDF shows the likelihood of a single value occurring, while the CDF shows the likelihood of a range of values occurring.

5. Can the CDF for Continuous RVs be used to find the probability of a specific value?

No, the CDF for Continuous RVs gives the cumulative probability up to a certain value, but it does not give the probability of a specific value. To find the probability of a specific value, you would need to use the PDF or a different method, such as the Probability Mass Function (PMF) for discrete random variables.

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