Estimation

Estimating the Mean

Estimating the Variance

Definition and Basic Concept

Estimate: is the result on a specific number or quantity from a statistic like a mean sample, percent, or variance of a sample

estimator: so the mean sample is the estimator mean of the population, percent of the sample is the estimator of a population percent

Estimation: is the whole process to resulting a estimate from a parameter, there are to estimate: point estimate and Interval estimate

A point estimate of some population parameter θ is a single value ˆθ of a statistic

Θ. For example, the value ¯ ˆ x of the statistic X¯, computed from a sample of size n,

is a point estimate of the population parameter μ

If Θˆ 1 and Θˆ 2 are two unbiased estimators of the same population parameter θ, we
want to choose the estimator whose sampling distribution has the smaller variance.

σθ1^2>σθ2^2. θ1 is more efficient estimator

If we consider all possible unbiased estimators of some parameter θ, the one with
the smallest variance is called the most efficient estimator of θ.

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the sample
mean ¯x will be used as a point estimate for the population mean μ

Recall that σX¯^2 = σ2/n, so a large sample will yield a value of X¯ that comes from a sampling, distribution with a small variance.

¯x is likely to be a very accurate estimate
of μ when n is large

According to the Central Limit Theorem, we can expect the sampling distribution of X¯ to be approximately normally distributed with mean μX=μ. standard deviation σX¯ = σ/√n

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A random sample of size n is selected from a population whose variance σ2 is known,
and the mean ¯x is computed to give the 100(1 − α)% confidence interval below

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confidence interval

Point estimate: from parameter θ os a single number that can be conclude as a number that make sense for θ

Interval Estimation: from a θ parameter, there's a random number that were used to estimate V. This process is called the interval estimation

image

Clearly, the values of the random variables Θˆ L and Θˆ U ,
are the confidence limits

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Reference: Harinaldi & Walpole 9th edition

Nadine Alifyarini 2006517556