Unbiased Least Square Estimate Vs. Biased Maximum Likelihood Estimate
Both
and
are used in different contexts. The former can give an unbiased to estimate when the two groups share an equal population variance. The latter one can give a more efficient to estimate biasedly. Note that the quantities in the right hand sides of both equations are the unbiased estimates.
Read more about this topic: Pooled Variance
Famous quotes containing the words unbiased, square, estimate, biased, maximum and/or likelihood:
“There is not a more disgusting spectacle under the sun than our subserviency to British criticism. It is disgusting, first, because it is truckling, servile, pusillanimous—secondly, because of its gross irrationality. We know the British to bear us little but ill will—we know that, in no case do they utter unbiased opinions of American books ... we know all this, and yet, day after day, submit our necks to the degrading yoke of the crudest opinion that emanates from the fatherland.”
—Edgar Allan Poe (1809–1845)
“I would say it was the coffin of a midget
Or a square baby
Were there not such a din in it.”
—Sylvia Plath (1932–1963)
“It is, indeed, at home that every man must be known by those who would make a just estimate either of his virtue or felicity; for smiles and embroidery are alike occasional, and the mind is often dressed for show in painted honour, and fictitious benevolence.”
—Samuel Johnson (1709–1784)
“Scientists are human—they’re as biased as any other group. But they do have one great advantage in that science is a self-correcting process.”
—Cyril Ponnamperuma (b. 1923)
“I had a quick grasp of the secret to sanity—it had become the ability to hold the maximum of impossible combinations in one’s mind.”
—Norman Mailer (b. 1923)
“Sustained unemployment not only denies parents the opportunity to meet the food, clothing, and shelter needs of their children but also denies them the sense of adequacy, belonging, and worth which being able to do so provides. This increases the likelihood of family problems and decreases the chances of many children to be adequately prepared for school.”
—James P. Comer (20th century)