For the bivariate random variable (X,Y), let the joint probability density function be \( f(x, y) = \frac{9(1 + x + y)}{2(1 + x)^4(1 + y)^5} \) for \( 0 < x < \infty, 0 < y < \infty \). The marginal pdf of X is:
\(\frac{3(2x+3)}{4(1+x)^4}\)
To find the marginal pdf of X, we integrate the joint pdf over all possible values of Y:
\[ f_X(x) = \int_{0}^{\infty} f(x,y) \, dy = \int_{0}^{\infty} \frac{9(1 + x + y)}{2(1 + x)^4(1 + y)^4} \, dy \]
Factor out terms not involving y:
\[ f_X(x) = \frac{9}{2(1 + x)^4} \int_{0}^{\infty} \frac{1 + x + y}{(1 + y)^4} \, dy \]
Split the integral:
\[ = \frac{9}{2(1 + x)^4} \left[ (1 + x) \int_{0}^{\infty} \frac{1}{(1 + y)^4} dy + \int_{0}^{\infty} \frac{y}{(1 + y)^4} dy \right] \]
Compute each integral separately:
1. \(\int \frac{1}{(1 + y)^4} dy = -\frac{1}{3(1 + y)^3}\)
Evaluated from 0 to ∞: \(0 - (-\frac{1}{3}) = \frac{1}{3}\)
2. \(\int \frac{y}{(1 + y)^4} dy\) (use substitution u = 1 + y):
\(= \int \frac{u-1}{u^4} du = \int (u^{-3} - u^{-4}) du = -\frac{1}{2u^2} + \frac{1}{3u^3}\)
Evaluated from 1 to ∞: \((0 + 0) - (-\frac{1}{2} + \frac{1}{3}) = \frac{1}{6}\)
Combine results:
\[ f_X(x) = \frac{9}{2(1 + x)^4} \left[ (1 + x)\cdot\frac{1}{3} + \frac{1}{6} \right] \]
\[ = \frac{9}{2(1 + x)^4} \left[ \frac{1 + x}{3} + \frac{1}{6} \right] \]
\[ = \frac{9}{2(1 + x)^4} \cdot \frac{2 + 2x + 1}{6} \]
\[ = \frac{9}{2(1 + x)^4} \cdot \frac{3 + 2x}{6} \]
\[ = \frac{9(3 + 2x)}{12(1 + x)^4} \]
\[ = \frac{3(3 + 2x)}{4(1 + x)^4} \]
\[ = \frac{3(2x + 3)}{4(1 + x)^4} \]
The correct answer is option 4: \(\frac{3(2x + 3)}{4(1 + x)^4}\)
Let X and Y have the joint p.m.f. f(x, y) = x + y / 21, where x = 1, 2, 3 and y = 1, 2. The marginal p.m.f. of X is:
Let the joint probability density function of \( (X, Y) \) be
\[f(x, y) = \begin{cases} 6xy^2 & \text{if } 0 < x < 1, 0 < y < 1 \\ 0, & \text{otherwise} \end{cases}\]
Then \( P\left(\frac{1}{2} < X < \frac{3}{4}\right) \) is:
For a random variable X following Poisson distribution with parameter 5, the variance of X is:
If \( n \) is a natural number, then, for what value of \( k \) is the following function a probability mass function?
\[ f(x) = \frac{n!}{x!(n-x)!}k^{x}(1-k)^{n-x}, \quad x = 0,1,2,\ldots,n \]
Let \( X \) have pdf:
\[ f(x) = \begin{cases} \frac{3(2x - x^2)}{4} & \text{for } 0 \leq x \leq 2, \\ 0, & \text{otherwise} \end{cases} \]
Then the mode is equal to:
A random variable X is distributed at random between the values 0 and 1 in such a way that the PDF of X is f(x) = x2(1 - x3), where k is a constant. The value of k is:
If the first two raw moments of X are equal to zero, then P(X = 0) is equal to:
Let the probability density function of \( X \) be:
\[ f(x) = \begin{cases} 3(1-x)^2 & \text{for } 0 \leq x \leq 1 \\ 0 & \text{otherwise} \end{cases} \]
Then \( P\left(\frac{1}{2} < X < \frac{3}{4}\right) \) is equal to:
In an industry, the risk of suffering from occupational disease is 20%. The probability that out of 6 workers, four will suffer from the disease is:
Let the probability mass function of \( X \) be given by:
Then the constant \( c \) is equal to:
Which of the following are the properties of Binomial distribution?
A. May be symmetrical or skewed
B. Uni-modal, bell-shaped and symmetrical
C. Asymptotic to the x-axis
D. n and p are the two parameters
E. μ and σ are the two parameters
Choose thecorrectanswer from the options given below:
The following two statements relate to probability distributions. Choose the correct code for the statements being correct or incorrect.
Statement I: When ‘p' and 'q' are equal in the binomial distribution, the shape of the distribution is perfectly symmetrical irrespective of the size of 'n'.
Statement II: The mean and the variance of Poisson distribution are not equal.
Which of the following are the properties of normal distribution?
(A) May be symmetrical or skewed
(B) Uni-modal, bell-shaped and symmetrical
(C) Asymptotic to the x-axis
(D) m and p are the two parameters
(E) μ and σ are the two parameters
Choose the correct answer from the options given below:
A discrete random variable X has the following probability distribution.
| X | 1 | 2 | 3 | 4 | 5 | 6 | 7 |
| P(X) | K | 2K | 2K | 3K | K 2 | 2K 2 | 7K 2 + K |
What is the value of K?
Match List - I with List - II :
| List - I (Description) | List - II (Term) |
|---|---|
| A. The probability of both success and failure remains constant | I. Binomial Distribution |
| B. The mean of distribution may be negative or positive | II. Poisson Distribution |
| C. The sum of all probabilities is equal to 1 | III. Normal Distribution |
| D. The probability of occurrence of an outcome within a very small time period is very small | IV. Random Variable |
Choose the correct answer from the options given below :