Question

Estimator bias occurs when a sample is not random and does not accurately represent the population being studied. a) True b) False

Answer 1

Estimator bias occurs when a sample is not random and does not accurately represent the population being studied. This statement is True.

Step-by-step explanation:

Estimator bias occurs when a sample is not random and does not accurately represent the population being studied. This statement is True. Estimator bias refers to the systematic deviation of an estimator from the true value of the population parameter. When a sample is biased, it means that certain members of the population are more likely to be included in the sample, leading to inaccurate conclusions about the entire population.

Answer 2

Estimator bias occurs when the method of estimation systematically overestimates or underestimates the targeted population parameter. A non-random sample can lead to bias, but it is not the sole source of estimator bias.

Step-by-step explanation:

Estimator bias refers to the systematic error that occurs when an estimator doesn't accurately estimate the population parameter it is intended to measure. The statement in the question is false. Estimator bias occurs not just because a sample is not random, but because the method of estimation itself systematically overestimates or underestimates the true population parameter. Having a non-random sample can lead to bias, but it's not the only source of bias; biases can also stem from the way data is collected, how outliers are handled, and numerous other factors in the estimation process. To counteract bias, it's essential to use randomized sampling methods and to ensure the sample is representative of the broader population.