Continuity Correction

نویسنده

  • Rabi Bhattacharya
چکیده

According to the central limit theorem (CLT ), the distribution function Fn of a normalized sum n(X1 + ... + Xn) of n independent random variables X1, ..., Xn , having a common distribution with mean zero and variance σ 2 > 0, converges to the distribution function Φσ of the normal distribution with mean zero and variance σ, as n → ∞. We will write Φ for Φ1 for the case σ = 1. The densities of Φσ and Φ are denoted by φσ and φ, respectively. In the case X ′ js are discrete, Fn has jumps and the normal approximation is not very good when n is not sufficiently large. This is a problem which most commonly occurs in statistical tests and estimation involving the normal approximation to the binomial and, in its multi-dimensional version, in Pearson’s frequency chisquare tests, or in tests for association in categorical data. Applying the CLT to a binomial random variable T with distribution B(n, p), with mean np and variance npq(q = 1 − p), the normal approximation is given , for integers 0 ≤ a ≤ b ≤ n, by P (a ≤ T ≤ b) ≈ Φ((b− np)/√npq)− Φ((a− np)/√npq). (1)

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تاریخ انتشار 2011