SACROWICZ & COHEN CRITERION
[Sacrowicz & Cohen()] This is a TAIL DEFINITION POLICY which asserts that the ALPHA value should be
A set of individual units, drawn from some definable POPULATION of units, and generally a small proportion of the POPULATION, to be used for a statistical examination of which the findings are intended to be applied to the POPULATION. It is essential for such inference that the SAMPLE should be REPRESENTATIVE. In RE-RANDOMISATION STATISTICS the process of applying inferences based upon the SAMPLE to the POPULATION is essentially informal.
The number of experimental units on which observations are considered. This may be less than the number of observations in a data-set, due to the possible multipying effects of multiple variables and/or REPEATED MEASURES within the EXPERIMENTAL DESIGN.
See MEASUREMENT TYPE.
[()]. ALGORITHMs employing BRANCH-AND-BOUND methods for the PTIMAN PERMUTAION TEST(1) and the PITMAN PERMUTATION TEST(2).
See : STATISTICAL SIGNIFICANCE.
STANDARD PROGRAMMING LANGUAGE
A PROGRAMMING LANGUAGE which has a publicly agreed common form across several different types of COMPUTER. Such standardisation allows a PROGRAM to be transported conveniently between the different types of COMPUTER and is thus suitable for communicating general ideas about programming. Some STANDARD PROGRAMMING LANGUAGES relevant to the present context are : FORTRAN, PASCAL, 'C'. There are a number of widely available programs for translating SOURCE PROGRAMS from one STANDARD PROGRAMMING LANGUAGE to another - e.g. the program PAS2C which translates source code from PASCAL to 'C'. Also see : ALGORITHM(2), ANSI, ISO.
A number or code derived by a prior-defined consistent process of calculation, from a set of data. Also see : ALGORITHM(1), TEST STATISTIC.
See : ALPHA, NOMINAL ALPHA CRITERION LEVEL.
[()] This is widely-observed scheme of distinctions between types of MEASUREMENT SCALEs according to the meaningfulness of arithmetic which may be performed upon data values. The types are : NOMINAL SCALE versus ORDINAL SCALE versus INTERVAL SCALE versus RATIO SCALE.
This is a feature of an EXPERIMENTAL DESIGN whereby a scheme of observations is repeated entirely using further sets (strata) of experimental units, with each such further set distinguished by a level of a categorical variable which is distinct from any categorical variables used to define the EXPERIMNATL DESIGN within a single set (stratum). The data from the various strata are regarded as distinct. This situation occurs when attempting to make inferences based upon the results of several similar independent experiments. Also see : REPEATED MEASURES, REPLICATIONS.