Choosing a good estimator
{"Image DocumentName": "Choosing a good estimator", "Image ImageDescription": "You can technically use any equation you want as a point estimator, but the most popular ones have certain desirable properties. Unbiasedness: The sampling distribution for the estimator \u2018centers\u2019 around the parameter. (On average, the estimator gives the correct value for the parameter.) Efficiency: If at the same sample size one unbiased estimator has a smaller sampling error than another unbiased estimator, the first one is more efficient. Consistency: The value of the estimator gets closer to the parameter as sample size increases. Consistent estimators may be biased, but the bias must become smaller as the sample size increases if the consistency property holds true.", "Image XResolution": "37", "Image YResolution": "37", "Image ResolutionUnit": "Pixels/Centimeter", "Image Software": "SlidePlayer", "Image YCbCrPositioning": "Centered"}