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In statistics, the two-way analysis of variance (ANOVA) is an extension of the one-way ANOVA that examines the influence of two different categorical independent variables on one continuous dependent variable. The two-way ANOVA not only aims at assessing the main effect of each independent variable but also if there is any interaction between them.
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 image above depicts a visual comparison between multivariate analysis of variance (MANOVA) and univariate analysis of variance (ANOVA). In MANOVA, researchers are examining the group differences of a singular independent variable across multiple outcome variables, whereas in an ANOVA, researchers are examining the group differences of sometimes multiple independent variables on a singular ...
The most common setting for Tukey's test of additivity is a two-way factorial analysis of variance (ANOVA) with one observation per cell. The response variable Y ij is observed in a table of cells with the rows indexed by i = 1,..., m and the columns indexed by j = 1,..., n. The rows and columns typically correspond to various types and levels ...
It was named after Student (1927), [2] D. Newman, [3] and M. Keuls. [4] This procedure is often used as a post-hoc test whenever a significant difference between three or more sample means has been revealed by an analysis of variance (ANOVA). [1] The Newman–Keuls method is similar to Tukey's range test as both procedures use studentized range ...
The integrated circuit sensor may come in a variety of interfaces — analogue or digital; for digital, these could be Serial Peripheral Interface, SMBus/I 2 C or 1-Wire.. In OpenBSD, many of the I 2 C temperature sensors from the below list have been supported and are accessible through the generalised hardware sensors framework [3] since OpenBSD 3.9 (2006), [4] [5]: §6.1 which has also ...
In statistics, Dunnett's test is a multiple comparison procedure [1] developed by Canadian statistician Charles Dunnett [2] to compare each of a number of treatments with a single control. [ 3 ] [ 4 ] Multiple comparisons to a control are also referred to as many-to-one comparisons.
In statistics, Scheffé's method, named after American statistician Henry Scheffé, is a method for adjusting significance levels in a linear regression analysis to account for multiple comparisons. It is particularly useful in analysis of variance (a special case of regression analysis), and in constructing simultaneous confidence bands for ...