Statistical Sciences 2141A/B Lecture 21: Section 7.2

• School: Western University
• Department: Statistical Sciences
• Course: Statistical Sciences 2141A/B
• Professor: Joe Raaymakers

Document Summary

If we write then an accurate estimator would be one resulting in small estimation errors, so that estimated values will be near the true value. If a point estimate is not unbiased, then its bias is defined as. "if the expected value of the parameter is equal to the parameter itself for every value of that expected parameter" Unbiasedness is a good property for a point estimate to possess, but otherwise, the smaller the absolute value of the bias, the better (although variance may also be a factor) Consider the unknown parameter p, which represents the probability that a machine breakdown is due to operator misuse. Suppose that a representative sample of n = 46 machine breakdowns is recorded, of which x = 13 are due to operator misuse. So, the above example can be applied to all circumstances. Therefore, the sample proportion is always an unbiased estimator of the population proportion a.