{[ promptMessage ]}

Bookmark it

{[ promptMessage ]}

# LL3 - variance obtained from a particular sample is a point...

This preview shows pages 1–2. Sign up to view the full content.

BUUS1200-3 1 Part 3 Introduction to Estimation 1. Point Estimation and Interval Estimation 2. Interval Estimation of Normal Population Mean: σ 2 Known 3. Determining the Sample Size Section 3.1 Point Estimation and Interval Estimation In point estimation we make use of a random variable depending on samples drawn from a population, called a point estimator, to compute a value that serves as a point estimate of a population parameter. Example 1 X can be a point estimator of the population mean µ . The actual value x , the sample mean obtained from a particular sample, is a point estimate of µ . S 2 can be a point estimator of the population variance σ 2 . The actual value s 2 , the sample BUUS1200-3 2 variance obtained from a particular sample, is a point estimate of σ 2 . If the expectation of the point estimator is equal to the population parameter being estimated, the point estimator is said to be an unbiased estimator of the population parameter. The value of an unbiased estimator of a population parameter is an unbiased estimate of the population parameter. We know from Section 2.3 that E( X ) = μ and E( S 2 ) = σ 2 . Therefore X is an unbiased estimator of µ and S 2 is an unbiased estimator of σ 2 . Note that S is not an unbiased estimator of the population standard deviation σ . An unbiased estimate is not necessarily equal to the population parameter to be estimated.

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}

### Page1 / 2

LL3 - variance obtained from a particular sample is a point...

This preview shows document pages 1 - 2. Sign up to view the full document.

View Full Document
Ask a homework question - tutors are online