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