Question

Explain the difference between measurement bias and estimation bias, where measurement bias is the tendency for samples to differ from their true value due to the method of measurement (e.g. uncalibrated scale).

Answer 1

Bias is the tendency of a statistic to overestimate or underestimate a parameter.

Measurement bias : Measurement errors are where a provided response is different from the real value. For example, you might survey to find out if a person voted for President Obama. A person may have voted for him, but they are confused by the wording of the questionnaire and mistakenly respond that they did not vote for him. Several factors may cause measurement error, including:

• The way the interviewer poses the question.
• The wording on the questionnaire.
• The way the data is collected.
• The respondent’s record-keeping system.   

Estimation bias: An Estimator is a rule for calculating an estimate of a quantity based on observed data. For example, you might have a rule to calculate a population mean. The result of using the rule is an estimate (a statistic) that hopefully is a true reflection of the population. The bias of an estimator is the difference between the statistic’s expected value and the true value of the population parameter. If the statistic is a true reflection of a population parameter it is an unbiased estimator. If it is not a true reflection of a population parameter it is a biased estimator.