Product Description
Originally published in 1922.This volume from the Cornell University Library's print collections was scanned on an APT BookScan and converted to JPG 2000 format by Kirtas Technologies.All titles scanned cover to cover and pages may include marks notations and other marginalia present in the original volume. ... Read more

Product Description
High Quality Content by WIKIPEDIA articles! In statistics, the Neyman-Pearson lemma states that when performing a hypothesis test between two point hypotheses H0: ? = ?0 and H1: ? = ?1, then the likelihood-ratio test which rejects H0 in favour of H1 when Lambda(x)=frac{ L( theta _{0} mid x)}{ L (theta _{1} mid x)} leq eta text{ where } P(Lambda(X)leq eta|H_0)=alphais the most powerful test of size ? for a threshold ?. If the test is most powerful for all theta_1 in Theta_1, it is said to be uniformly most powerful (UMP) for alternatives in the set Theta_1 , . It is named for Jerzy Neyman and Egon Pearson. In practice, the likelihood ratio is often used directly to construct tests ? see Likelihood-ratio test. However it can also be used to suggest particular test-statistics that might be of interest or to suggest simplified tests ? for this one considers algebraic manipulation of the ratio to see if there are key statistics in it is related to the size of the ratio (i.e. whether a large statistic corresponds to a small ratio or to a large one). ... Read more