CDF of a function of 2 random variables

In summary: The events (T1 <= x and T2 <= T1) and (T2 <= x and T1 <= T2) are independent (why?), so the P(... OR ...) above is equal to the sum of the P(...)'s.The first P(...) is a bit easier to calculate: it's just ##P(T1 <= x) * P(T2 <= T1)##. The second P(...) you can calculate by symmetry: it's equal to the first one, because T1 and T2 are completely interchangeable.So you get##P(T \leq x) = P(T1 <= x) * P(T2 <= T1) + P(T2 <= x) * P(T1 <=
  • #1
vortmax
19
1

Homework Statement


Two toys are started at the same time each with a different battery. The first battery has a lifetime that is exponentially distributed with mean 100 min; the second battery has a lifetime that is Rayleigh-distributed with a mean 100 minutes.

a) Find the CDF to the time T until the battery in a toy first runs out
b) Suppose that both toys are still operational at 100 minutes. Find the CDF of the time T2 that subsequently elapses until the battery in a toy first runs out
c) in part b, find the cdf to the total time that elapses until a battery first fails.


Homework Equations



Exponential Dist

[itex]f(T) = \lambda e^{-\lambda T}[/itex]
[itex] F(T) = 1 - e^{-\lambda T}[/itex]

Rayleigh-dist

[itex]f(T) = \frac{T}{\alpha^2} e^{\frac{-T}{2\alpha^2}}[/itex]
[itex]F(T) = 1 - e^{\frac{-T}{2\alpha^2}}[/itex]


The Attempt at a Solution



First, I calculated values for lambda and alpha based on the means ... but this part isn't entirely necessary to the final solution.

a) I need to find the cdf of the function:

[itex] T = min(T_1,T_2)[/itex]

where [itex]T_1[/itex] and [itex]T_2[/itex] are the two RV's respectively... but I'm really at a loss about how to proceed.
 
Physics news on Phys.org
  • #2
first time uses
 
  • #3
This is a special case of what is called "order statistics", the lowest, 2nd lowest, 3rd lowest, of a set of random variables. You can google on that keyword to learn more about how they're calculated.

##T \leq x## means either T1 is the smallest and is ##\leq x##, or T2 is the smallest and is ##\leq x##.

So ##P(T \leq x) = P[ (T1 \leq x \text{ and } T2 <= T1) \text{ OR } (T2 \leq x \text{ and } T1 \leq T2) ]##
 

FAQ: CDF of a function of 2 random variables

What is the CDF of a function of 2 random variables?

The CDF (Cumulative Distribution Function) of a function of 2 random variables is a mathematical function that describes the probability of a certain value or range of values occurring for the function of the 2 variables. It is used to determine the likelihood of a particular outcome in a statistical experiment.

How is the CDF of a function of 2 random variables calculated?

The CDF of a function of 2 random variables is calculated by integrating the joint probability density function (PDF) of the 2 variables over a specified range. This involves finding the area under the curve of the PDF within the given range of values.

What is the relationship between the CDF and the PDF of a function of 2 random variables?

The CDF and PDF of a function of 2 random variables are closely related. The CDF is the integral of the PDF, meaning that the CDF describes the cumulative probability of a range of values while the PDF describes the probability of a single value.

How is the CDF of a function of 2 random variables used in statistical analysis?

The CDF of a function of 2 random variables is used in statistical analysis to determine the probability of a specific outcome occurring. It can also be used to calculate the expected value and variance of the function of the 2 variables.

Can the CDF of a function of 2 random variables be used to find the probability of a certain event?

Yes, the CDF of a function of 2 random variables can be used to find the probability of a certain event by calculating the area under the curve of the CDF within the range of values corresponding to the event. This is known as the probability of the event occurring.

Similar threads

Back
Top