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Cochran, William G. (1977). Sampling Techniques (Third ed.). Wiley. ISBN 0-471-16240-X. Statistical Methods Applied to Experiments in Agriculture and Biology by George W. Snedecor (Cochran contributed from the fifth (1956) edition) ISBN 0-8138-1561-4; Planning and Analysis of Observational Studies (edited by Lincoln E. Moses and Frederick ...
The first of these sampling schemes is a double use of a sampling method introduced by Lahiri in 1951. [14] The algorithm here is based upon the description by Lohr. [13] Choose a number M = max( x 1, ..., x N) where N is the population size. Choose i at random from a uniform distribution on [1,N]. Choose k at random from a uniform distribution ...
Statistical Methods. Author: George W. Snedecor Publication data: 1937, Collegiate Press Description: One of the first comprehensive texts on statistical methods. Reissued as Statistical Methods Applied to Experiments in Agriculture and Biology in 1940 and then again as Statistical Methods with Cochran, WG in 1967. A classic text.
This is since stratified sampling removes some of the variability in the specific number of elements per stratum, as occurs under SRS. [citation needed] Relatedly, Cochran (1977) provides a formula for the proportional increase in variance due to deviation from optimum allocation (what, in Kish's formulas, would be called L). [3]: 116
Cochran's test, [1] named after William G. Cochran, is a one-sided upper limit variance outlier statistical test .The C test is used to decide if a single estimate of a variance (or a standard deviation) is significantly larger than a group of variances (or standard deviations) with which the single estimate is supposed to be comparable.
In statistics, Cochran's theorem, devised by William G. Cochran, [1] is a theorem used to justify results relating to the probability distributions of statistics that are used in the analysis of variance.
Cochran's test is a non-parametric statistical test to verify whether k treatments have identical effects in the analysis of two-way randomized block designs where the response variable is binary. [ 1 ] [ 2 ] [ 3 ] It is named after William Gemmell Cochran .
The Cochran–Armitage test for trend, [1] [2] named for William Cochran and Peter Armitage, is used in categorical data analysis when the aim is to assess for the presence of an association between a variable with two categories and an ordinal variable with k categories.