Skip to main content

Estimation Bias

Edited by: Published: 2018
+- LessMore information
Download PDF

Estimation bias, or simply bias, is a concept in statistical inference that relates to the accuracy of parameter estimation. The term bias was first introduced in the statistical context by English statistician Sir Arthur L. Bowley in 1897. This entry provides the formal definition of estimation bias along with the concept of error, its implications and uses in statistical inference, and relevance to other types of bias that may arise in the data collection process.

The Concept ofError in Statistical Inference

Suppose that we would like to estimate a population parameter θ (e.g., population mean). An estimator θ^ is any sample statistic (e.g., sample mean) that is used to estimate θ. Because θ^ is sample based, it does not perfectly agree with the true value of θ. ...

Looks like you do not have access to this content.

Reader's Guide

  • All
  • A
  • B
  • C
  • D
  • E
  • F
  • G
  • H
  • I
  • J
  • K
  • L
  • M
  • N
  • O
  • P
  • Q
  • R
  • S
  • T
  • U
  • V
  • W
  • X
  • Y
  • Z

      Copy and paste the following HTML into your website