# In Example 12.4.1, in contrast to Example 10.2.1, when we introduced the contaminated distribution for Îµi, we did not introduce a bias. Show that if we had, it would not have mattered. That is, if we assume then: (a) The least squares estimator b would still be an unbiased estimator of Î². (b) The least squares estimator a has expectation

In Example 12.4.1, in contrast to Example 10.2.1, when we introduced the contaminated distribution for Îµi, we did not introduce a bias. Show that if we had, it would not have mattered. That is, if we assume

then:
(a) The least squares estimator b would still be an unbiased estimator of Î².
(b) The least squares estimator a has expectation Î± + Î´Î¼, so the model may just as well be assumed to be Yi = Î± + Î´Î¼ + Î²xi + Îµi.

Distribution
The word "distribution" has several meanings in the financial world, most of them pertaining to the payment of assets from a fund, account, or individual security to an investor or beneficiary. Retirement account distributions are among the most...

## This problem has been solved!

Do you need an answer to a question different from the above? Ask your question!
Related Book For

## Statistical Inference

2nd edition

Authors: George Casella, Roger L. Berger

ISBN: 978-0534243128