let random variable X be an expoentital random variable with PDF 7e^(-7x). let Y be another indepednent exponential random varaible with PDF 7e^(-7y). Find the pdf of W=X+Y
let random variable X be an expoentital random variable with PDF 7e^(-7x). let Y be another indepednent exponential random varaible with PDF 7e^(-7y). Find the pdf of W=X+Y
user
Sure, I'd be happy to help! Let's dive into this question.

To start, we know that X and Y are both exponential random variables with PDFs of $7e^{-7x}$ and $7e^{-7y}$, respectively. To find the PDF of W = X + Y, we need to use the sum rule for exponential distributions.

The sum rule states that if X and Y are independent exponential random variables with rates λ1 and λ2, respectively, then the sum W = X + Y has a PDF given by:

PDF(W) = λ1 + λ2

In this case, we have λ1 = λ2 = 7, since the rate parameter for both X and Y is 7. Therefore, the PDF of W = X + Y is:

PDF(W) = 7 + 7 = 14

So, the PDF of W = X + Y is a rectangular distribution with a rate parameter of 14.

I hope this helps! Let me know if you have any other questions or if there's anything else I can help with.
assistant
let random variable X be an expoentital random variable with PDF 7e^(-7x). let Y be another indepednent exponential random varaible with PDF 7e^(-7y). Find the pdf of W=X+Y
user
To find the PDF of W = X + Y, we can use the convolution property of independent random variables. The convolution property states that the PDF of the sum of two independent random variables is given by the convolution of their respective PDFs.

Given that X has PDF f_X(x) = 7e^(-7x) and Y has PDF f_Y(y) = 7e^(-7y), we want to find the PDF of W, which we'll call f_W(w).

The convolution of two functions f(x) and g(x) is given by:

f * g(x) = ∫∫ f(x - y) g(y) dy dx

Applying the convolution property to our problem, we have:

f_W(w) = f_X(w - y) * f_Y(y) dy dx

We can simplify this expression by changing the limits of integration. Let's change the variable of integration in the second integral from y to z = 7y:

f_W(w) = ∫ f_X(w - z) * 7e^(-7z) dz

Now, we need to find the PDF of X conditionally on W = w. Since X and Y are independent, we know that X has the same distribution as W - Y. Therefore, we can write:

f_X(w - z) = f_W(w) / 7

Substituting this expression back into our integral, we get:

f_W(w) = (1 / 7) * ∫ 7e^(-7z) * f_W(w) dz

Rearranging the terms, we obtain an ordinary differential equation (ODE):

f_W(w) * 7 = 7e^(-7z) * f_W(w)

Dividing both sides by 7, we get:

f_W(w) = e^(-7z)

Now, we need to find the inverse function z(w) such that w = z(w) + y, where y is a constant. In this case, z(w) = (w - 7y) / 7. Substituting this expression back into our ODE, we obtain:

f_W(w) = e^(w - 7y)

Thus, the PDF of W = X + Y is:

f_W(w) = e^(w - 7y) / 7
assistant
let random variable X be an expoentital random variable with PDF 7e^(-7x). let Y be another indepednent exponential random varaible with PDF 7e^(-7y). Find the pdf of W=X+Y
user
Sure, I'd be happy to help! Let's dive into this question.

To start, we know that X and Y are both exponential random variables with PDFs of $7e^{-7x}$ and $7e^{-7y}$, respectively. To find the PDF of W = X + Y, we need to use the sum rule for exponential distributions.

The sum rule states that if X and Y are independent exponential random variables with rates λ1 and λ2, respectively, then the sum W = X + Y has a PDF given by:

PDF(W) = λ1 + λ2

In this case, we have λ1 = λ2 = 7, since the rate parameter for both X and Y is 7. Therefore, the PDF of W = X + Y is:

PDF(W) = 7 + 7 = 14

So, the PDF of W = X + Y is a rectangular distribution with a rate parameter of 14.

I hope this helps! Let me know if you have any other questions or if there's anything else I can help with.
assistant
<|system|>
 
<|user|>
let random variable X be an expoentital random variable with PDF 7e^(-7x). let Y be another indepednent exponential random varaible with PDF 7e^(-7y). Find the pdf of W=X+Y 
<|assistant|>
The sum of two independent exponential random variables X and Y is also an exponential random variable with parameter λ = 7. Therefore, the pdf of W=X+Y is given by:

f_w(w) = λe^(-λw) = 7e^(-7w)

where λ = 7 and w is the random variable representing the sum of X and Y, i.e., W = X + Y. The corresponding pdf of W is:

f_w(w) = 7e^{-7w}

Therefore, the pdf of W=X+Y is given by:

f_w(w) = 7e^{-7w}
To find the PDF of W=X+Y, we can use the convolution theorem for exponential distributions. The convolution theorem states that if X and Y are independent exponential random variables with PDFs f_X(x) and f_Y(y), respectively, then the PDF of W=X+Y is given by:

f_W(w) = ∫ f_X(x) f_Y(w-x) dx

In this case, we have:

f_W(w) = ∫ 7e^(-7x) 7e^(-7(w-x)) dx

= 7e^(-7w) ∫ e^(7x) dx

= 7e^(-7w) (1/7)e^(7x) |x=0

= 7e^(-7w)

Therefore, the PDF of W=X+Y is 7e^(-7w).
To find the PDF of W=X+Y, we can use the convolution theorem for probability distributions. The convolution theorem states that if X and Y are two independent random variables with PDFs f_X(x) and f_Y(y), respectively, then the PDF of their sum W=X+Y is given by:

f_W(w) = ∫ f_X(x) f_Y(w-x) dx

In this case, X and Y are both exponential random variables with the same rate parameter 7. Therefore, their PDFs are:

f_X(x) = 7e^{-7x}
f_Y(y) = 7e^{-7y}

Using the convolution theorem, we have:

f_W(w) = ∫ f_X(x) f_Y(w-x) dx
= ∫ 7e^{-7x} 7e^{-7(w-x)} dx
= 7e^{-7w} ∫ e^{-7x} dx
= 7e^{-7w} (1/7) e^{-7x} |_0^w
= 7e^{-7w}

Therefore, the PDF of W=X+Y is also an exponential distribution with rate parameter 7.