Let 𝑋 be uniform on [0,1/2] . Find the PDF 𝑓𝑌(𝑦) of 𝑌=𝑋/(1−𝑋) .

For 0≤𝑦≤1, what is 𝑓𝑌(𝑦) ?

To find the PDF of Y, we first need to find the cumulative distribution function (CDF) of Y and then differentiate it to obtain the PDF.

Let's start by finding the CDF of Y.

The definition of the CDF of a random variable Y is given by:

F_Y(y) = P(Y ≤ y)

Since Y = X / (1 - X), we can rewrite the above equation as:

F_Y(y) = P(X / (1 - X) ≤ y)

Multiplying both sides of the inequality by (1 - X), we get:

F_Y(y) = P(X ≤ y * (1 - X))

Now, since X is uniformly distributed on [0, 1/2], its PDF is constant over this interval and equal to 2. Therefore, we can rewrite the above equation as an integral:

F_Y(y) = ∫[0, y*(1 - x)] 2 dx

Integrating with respect to x, we get:

F_Y(y) = 2∫[0, y*(1 - x)] dx

F_Y(y) = 2[x]_[0, y*(1 - x)]

F_Y(y) = 2[y*(1 - y) - 0]

F_Y(y) = 2y(1 - y)

Now, to find the PDF f_Y(y), we differentiate the CDF with respect to y:

f_Y(y) = d/dy [F_Y(y)]

f_Y(y) = d/dy [2y(1 - y)]

f_Y(y) = 2(1 - 2y)

Therefore, the PDF of Y, f_Y(y), for 0 ≤ y ≤ 1 is given by:

f_Y(y) = 2(1 - 2y)

To find the PDF of 𝑌, you need to follow these steps:

Step 1: Determine the cumulative distribution function (CDF) of 𝑌, 𝐹𝑌(𝑦).
Step 2: Differentiate the CDF to obtain the PDF, 𝑓𝑌(𝑦).

Let's find the CDF and then differentiate it to find the PDF.

Step 1: Calculate the CDF, 𝐹𝑌(𝑦):
To find the CDF of 𝑌, we need to find the probability that 𝑌 takes on a value less than or equal to 𝑦 (i.e., 𝑃(𝑌 ≤ 𝑦)).

Since 𝑌 = 𝑋 / (1 - 𝑋), we can write 𝑌(1 - 𝑋) = 𝑋.

Expanding the equation gives 𝑌 - 𝑌𝑋 = 𝑋, and rearranging gives 𝑋 = 𝑌 / (1 + 𝑌).

Now, we can express the inequality 𝑌 ≤ 𝑦 in terms of 𝑋:

𝑌 ≤ 𝑦
⇒ 𝑌 / (1 + 𝑌) ≤ 𝑦.

Solving this inequality for 𝑋, we get:

𝑋 ≤ 𝑌 / (1 + 𝑌).

Since 𝑋 is uniform on [0, 1/2], the probability that 𝑋 ≤ 𝑦 / (1 + 𝑦) is simply 𝑦 / (1 + 𝑦).

Therefore, the CDF of 𝑌, 𝐹𝑌(𝑦), is given by:

𝐹𝑌(𝑦) = 𝑦 / (1 + 𝑦), for 0 ≤ 𝑦 ≤ 1.

Step 2: Differentiate the CDF to obtain the PDF, 𝑓𝑌(𝑦):
To find the PDF, we differentiate the CDF with respect to 𝑦.

Differentiating 𝐹𝑌(𝑦) = 𝑦 / (1 + 𝑦) with respect to 𝑦 gives:

𝑓𝑌(𝑦) = d/d𝑦 (𝑦 / (1 + 𝑦)).

To differentiate this expression, we can use the quotient rule:

𝑓𝑌(𝑦) = [(1 + 𝑦) * d(𝑦) / d𝑦 - 𝑦 * d(1 + 𝑦) / d𝑦] / (1 + 𝑦)².

Simplifying, we have:

𝑓𝑌(𝑦) = (1 / (1 + 𝑦)²).

Therefore, the PDF of 𝑌, 𝑓𝑌(𝑦), for 0 ≤ 𝑦 ≤ 1 is:

𝑓𝑌(𝑦) = 1 / (1 + 𝑦)².