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The model for a randomized block design with one nuisance variable is = + + + where Y ij is any observation for which X 1 = i and X 2 = j X 1 is the primary factor X 2 is the blocking factor μ is the general location parameter (i.e., the mean)
In some cases, the data sets are paired, meaning there is an obvious and meaningful one-to-one correspondence between the data in the first set and the data in the second set, compare Blocking (statistics). For example, paired data can arise from measuring a single set of individuals at different points in time. [1]
To exploit variance reduction with paired samples, a paired permutation test must be applied, see paired difference test. This is equivalent to performing a normal, unpaired permutation test, but restricting the set of valid permutations to only those which respect the paired nature of the data by forbidding both halves of any pair from being ...
The Skillings–Mack test is a general Friedman-type statistic that can be used in almost any block design with an arbitrary missing-data structure. The Wittkowski test is a general Friedman-Type statistics similar to Skillings-Mack test. When the data do not contain any missing value, it gives the same result as Friedman test.
A paired difference test, better known as a paired comparison, is a type of location test that is used when comparing two sets of paired measurements to assess whether their population means differ. A paired difference test is designed for situations where there is dependence between pairs of measurements (in which case a test designed for ...
In this ranking, each of A, B, and C is the most preferable person for someone. In any solution, one of A, B, or C must be paired with D and the other two with each other (for example AD and BC), yet for anyone who is partnered with D, another member will have rated them highest, and D's partner will in turn prefer this other member over D. In ...
McNemar's test is a statistical test used on paired nominal data. It is applied to 2 × 2 contingency tables with a dichotomous trait, with matched pairs of subjects, to determine whether the row and column marginal frequencies are equal (that is, whether there is "marginal homogeneity"). It is named after Quinn McNemar, who introduced it in ...
If a variable is only referenced by a single identifier, that identifier can simply be called the name of the variable; otherwise, we can speak of it as one of the names of the variable. For instance, in the previous example the identifier "total_count" is the name of the variable in question, and "r" is another name of the same variable.