A random variable \(X\) is said to be distributed as…

GATE · 2025 · DA · Data Science & AI

A random variable XX is said to be distributed as Bernoulli⁡(θ)\operatorname{Bernoulli}(\theta), denoted by X∼Bernoulli⁡(θ)X\sim\operatorname{Bernoulli}(\theta), if P(X=1)=θ,P(X=0)=1−θP(X=1)=\theta,\quad P(X=0)=1-\theta for 0<θ<10<\theta<1. Let Y=∑i=1300XiY=\sum_{i=1}^{300}X_i, where Xi∼Bernoulli⁡(θ)X_i\sim\operatorname{Bernoulli}(\theta), i=1,2,…,300i=1,2,\ldots,300 are independent and identically distributed random variables with θ=0.25\theta=0.25. The value of P(60≤Y≤90)P(60\leq Y\leq 90), after approximation through Central Limit Theorem, is given by

(Recall that ϕ(x)=12π∫−∞xe−t2/2 dt\phi(x)=\frac{1}{\sqrt{2\pi}}\int_{-\infty}^{x}e^{-t^2/2}\,dt.)

  1. A.

    φ(2) − φ(−2)

  2. B.

    φ(1) − φ(−1)

  3. C.

    φ(3) − φ(−3)

  4. D.

    φ(90) − φ(60)

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