Mean and Variance of Binomial Distribution MCQ Quiz in தமிழ் - Objective Question with Answer for Mean and Variance of Binomial Distribution - இலவச PDF ஐப் பதிவிறக்கவும்
Last updated on Mar 17, 2025
Latest Mean and Variance of Binomial Distribution MCQ Objective Questions
Top Mean and Variance of Binomial Distribution MCQ Objective Questions
Mean and Variance of Binomial Distribution Question 1:
If X has Binomial distribution with parameters n and p such that np =λ, then \(\mathop {\lim }\limits_{n \to \infty } b\left( {x,n,p} \right);x = 0,1,2,.....\) is equal to:
Answer (Detailed Solution Below)
Mean and Variance of Binomial Distribution Question 1 Detailed Solution
Explanation
Poisson distributionis a limiting case of binomial distribution if it follows conditions
n, the number trials is indefinitely large that means n tends to infinite
p, the constant probability of success for each trial is indefinitely small p tends to 0
np = λ , is finite so λ/n = p, q = 1 – p
⇒ (1 – λ/n), λ is positive integer
The probability of x successes in a series of n independent trials is
⇒ b(x, n, p) = (n/x)pxqn – x, x = 0, 1, 2, 3…….n
⇒ b(x, n, p) = (n/x)px(1 – p)n – x
∴ (n/x)(p/(1 – p)]x(1 – p)n - x
p , the constant probability of success for each trial is indefinitely small p tends to 0
np = λ , is finite so λ/n = p, q = 1 – p
⇒ (1 – λ/n), λ is positive integer
The probability of x successes in a series of n independent trials is
⇒ b(x, n, p) = (n/x)pxqn – x, x = 0, 1, 2, 3…….n
⇒ b(x, n, p) = (n/x)px(1 – p)n – x
∴ (n/x)(p/(1 – p)]x(1 – p)n - x
⇒ [n(n - 1)(n - 2)------(n - x + 1)/x!] × (λ/n)x/(1 - λ /n)x[1 - λ/n]n
⇒ [(1 - 1/n)(1 - 2/n)-----( 1 - (x - 1)/n/x!(1 - λ/n)x] × λx[1 - λ/n]n
⇒ Lim x → ∞ b(x, n, p) = e-λ × λx/x! ; x = 0, 1, 2, 3, 4 -------,n
Poisson distribution = A random variables X is said to follow poisson distribution if it assumes only non - negative values and its proportionality mass function i s given
by P)X = x) = e-λ × λx/x! where x = 0, 1, 2, 3 ------n and λ > 0
⇒ p(x, λ) = ∑P(X - x)
⇒ e-λ∑λx/x!
⇒ e-λ× e-λ = 1
∴ The corresponding distribution function is F(x) = P(X = x) = ∑P(r) = e-λ ∑λ2/r!; x = 0, 1, 2 .......