Search results
Results From The WOW.Com Content Network
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").
In spatial analysis, four major problems interfere with an accurate estimation of the statistical parameter: the boundary problem, scale problem, pattern problem (or spatial autocorrelation), and modifiable areal unit problem. [1] The boundary problem occurs because of the loss of neighbours in analyses that depend on the values of the neighbours.
Multiple comparisons arise when a statistical analysis involves multiple simultaneous statistical tests, each of which has a potential to produce a "discovery". A stated confidence level generally applies only to each test considered individually, but often it is desirable to have a confidence level for the whole family of simultaneous tests. [ 4 ]
The following numerical example illustrates Lindley's paradox. In a certain city 49,581 boys and 48,870 girls have been born over a certain time period. The observed proportion of male births is thus 49 581 / 98 451 ≈ 0.5036. We assume the fraction of male births is a binomial variable with parameter .
In statistics and regression analysis, moderation (also known as effect modification) occurs when the relationship between two variables depends on a third variable. The third variable is referred to as the moderator variable (or effect modifier ) or simply the moderator (or modifier ).
Waiting time between eruptions and the duration of the eruption for the Old Faithful Geyser in Yellowstone National Park, Wyoming, USA. This scatterplot suggests there are generally two "types" of eruptions: short-wait-short-duration, and long-wait-long-duration. Bivariate analysis is one of the simplest forms of quantitative (statistical ...
Despite the name, it is weaker than the direct method of difference and does not include it. Symbolically, the Joint method of agreement and difference can be represented as: A B C occur together with x y z A D E occur together with x v w F G occur with y w —————————————————— Therefore A is the cause, or the ...
Random effects introduce statistical variability at different levels of the data hierarchy. These account for the unmeasured sources of variance that affect certain groups in the data. For example, the differences between student 1 and student 2 in the same class, or the differences between class 1 and class 2 in the same school. [9] [10] [11]