k=1 The sample variance is an unbiased estimator of o2. The sample standard deviation is defined as S = √S², and is commonly used as an estimator for o. Nevertheless, S is a biased estimator of σ.

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Let X₁, X2, X3, ..., Xn be a random sample with mean EX₁ = μ<∞, and
variance 0 < Var (X₂) = o² <oo. The sample variance of this random sample
is defined as
n
n
1
S²
1
(X-X) ²: (x²
Σx - nx
1-nt²
n-1
n-1
k=1
The sample variance is an unbiased estimator of o2. The sample standard
deviation is defined as
S = √S²,
and is commonly used as an estimator for o. Nevertheless, S is a biased
estimator of σ.
Transcribed Image Text:Let X₁, X2, X3, ..., Xn be a random sample with mean EX₁ = μ<∞, and variance 0 < Var (X₂) = o² <oo. The sample variance of this random sample is defined as n n 1 S² 1 (X-X) ²: (x² Σx - nx 1-nt² n-1 n-1 k=1 The sample variance is an unbiased estimator of o2. The sample standard deviation is defined as S = √S², and is commonly used as an estimator for o. Nevertheless, S is a biased estimator of σ.
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