Hello. I am stuck on a question and need some help, please. Anyone good with Stats?

Which of the following statements about estimators is correct:


A. All unbiased estimators for a parameter are equally good.


B. An unbiased estimator will always have a smaller MSE than a bias estimator.


C. A good estimator never gives a bad estimate.


D. A different estimator carries the absolute difference of an estimator from a base year estimate to a current year estimate.





I would like the correct answer, but would like to also know the reasoning, so that I can actually understand. I appreciate it :)|||A) false - unbiased esitmators can have different levels of variability and precision


B) false - you can have a biased estimator that has a lower MSE then an unbiased estimator


C) false - of course it depends on your definition of "bad" - but you can have a regression model, for example, that doesnt give a good estimate if the prediction is based on a value not that close to the mean


D) I dont uderstand this question