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Pseudoreplication, as originally defined, is a special case of inadequate specification of random factors where both random and fixed factors are present. [1]

7 relations: Analysis of variance, Confounding, Replication (statistics), Statistical hypothesis testing, Statistical significance, Statistical unit, Student's t-test.

Analysis of variance

Analysis of variance (ANOVA) is a collection of statistical models used to analyze the differences among group means and their associated procedures (such as "variation" among and between groups), developed by statistician and evolutionary biologist Ronald Fisher.

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In statistics, a confounding variable (also confounding factor, a confound, or confounder) is an extraneous variable in a statistical model that correlates (directly or inversely) with both the dependent variable and the independent variable.

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Replication (statistics)

In engineering, science, and statistics, replication is the repetition of an experimental condition so that the variability associated with the phenomenon can be estimated.

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Statistical hypothesis testing

A statistical hypothesis is a hypothesis that is testable on the basis of observing a process that is modeled via a set of random variables.

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Statistical significance

In statistics, statistical significance (or a statistically significant result) is attained when a ''p''-value is less than the significance level.

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Statistical unit

A unit in a statistical analysis refers to one member of a set of entities being studied.

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Student's t-test

A t-test is any statistical hypothesis test in which the test statistic follows a Student's ''t''-distribution if the null hypothesis is supported.

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N = 1 fallacy, N=1 fallacy.


[1] https://en.wikipedia.org/wiki/Pseudoreplication

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