An estimator is unbiased if it produces
A)a parameter from the sample that equals the true parameter.
B)estimates of a parameter that are close to the true parameter.
C)estimates of a parameter that are statistically significant.
D)estimates of a parameter that are on average equal to the true parameter.
E)both b and c

Question

Quizplus · Accepted Answer

An estimator is unbiased if its estimates of a parameter are on average equal to the true parameter. This means that if the estimator is used repeatedly to estimate the parameter, the average estimate will converge to the true parameter value. Being statistically significant (choice C) is not a requirement for unbiasedness, and choice A is not possible since a parameter is a fixed value and cannot be estimated from a sample. Choice B is a desirable property for any estimator but does not necessarily imply unbiasedness, and choice E is incorrect as well.

An Estimator Is Unbiased If It Produces