Mean and Variance of Binomial Distribution MCQ Quiz in मराठी - Objective Question with Answer for Mean and Variance of Binomial Distribution - मोफत PDF डाउनलोड करा

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पाईये Mean and Variance of Binomial Distribution उत्तरे आणि तपशीलवार उपायांसह एकाधिक निवड प्रश्न (MCQ क्विझ). हे मोफत डाउनलोड करा Mean and Variance of Binomial Distribution एमसीक्यू क्विझ पीडीएफ आणि बँकिंग, एसएससी, रेल्वे, यूपीएससी, स्टेट पीएससी यासारख्या तुमच्या आगामी परीक्षांची तयारी करा.

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:

  1. \({\frac{{{e^{^{ - \lambda }}}\lambda }}{{x!}}^x}\), x = 0, 1, 2, … 
  2. Limit does not exist
  3. 0
  4. 1

Answer (Detailed Solution Below)

Option 1 : \({\frac{{{e^{^{ - \lambda }}}\lambda }}{{x!}}^x}\), x = 0, 1, 2, … 

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× e = 1

∴ The corresponding distribution function is F(x) = P(X = x) = ∑P(r) =  e ∑λ2/r!; x = 0, 1, 2 .......

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