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Given a sample of size , a jackknife estimator can be built by aggregating the parameter estimates from each subsample of size () obtained by omitting one observation. [ 1 ] The jackknife technique was developed by Maurice Quenouille (1924–1973) from 1949 and refined in 1956.
False Discovery Rate: Corrected & Adjusted P-values - MATLAB/GNU Octave implementation and discussion on the difference between corrected and adjusted FDR p-values. Understanding False Discovery Rate - blog post
Mark and recapture is a method commonly used in ecology to estimate an animal population's size where it is impractical to count every individual. [1] A portion of the population is captured, marked, and released.
This test procedure is based on the statistic whose sampling distribution is approximately a Chi-Square distribution with (k − 1) degrees of freedom, where k is the number of random samples, which may vary in size and are each drawn from independent normal distributions. Bartlett's test is sensitive to departures from normality.
Let m be the size of the sample from the first population. Let m 1 be the number of observations (in the sample) in category #1; so the number of observations in category #2 is m − m 1. Similarly, let n be the size of the sample from the second population. Let n 1 be the number of observations (in the sample) in category #1.
The case that the x variable arises randomly is known as the structural model or structural relationship.For example, in a medical study patients are recruited as a sample from a population, and their characteristics such as blood pressure may be viewed as arising from a random sample.
The probability density function (PDF) for the Wilson score interval, plus PDF s at interval bounds. Tail areas are equal. Since the interval is derived by solving from the normal approximation to the binomial, the Wilson score interval ( , + ) has the property of being guaranteed to obtain the same result as the equivalent z-test or chi-squared test.
An alternative correction that is believed to be less conservative is the Huynh–Feldt correction (1976). As a general rule of thumb, the Greenhouse–Geisser correction is the preferred correction method when the epsilon estimate is below 0.75. Otherwise, the Huynh–Feldt correction is preferred. [3]