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  2. Mill's methods - Wikipedia

    en.wikipedia.org/wiki/Mill's_Methods

    Symbolically, the method of concomitant variation can be represented as (with ± representing a shift): A B C occur together with x y z A± B C results in x± y z. ————————————————————— Therefore A and x are causally connected. Unlike the preceding four inductive methods, the method of concomitant ...

  3. Concomitant (statistics) - Wikipedia

    en.wikipedia.org/wiki/Concomitant_(statistics)

    In statistics, the concept of a concomitant, also called the induced order statistic, arises when one sorts the members of a random sample according to corresponding values of another random sample. Let ( X i , Y i ), i = 1, . . ., n be a random sample from a bivariate distribution.

  4. Dunning–Kruger effect - Wikipedia

    en.wikipedia.org/wiki/Dunning–Kruger_effect

    Some researchers include a metacognitive component in their definition. In this view, the Dunning–Kruger effect is the thesis that those who are incompetent in a given area tend to be ignorant of their incompetence, i.e., they lack the metacognitive ability to become aware of their incompetence.

  5. Causal analysis - Wikipedia

    en.wikipedia.org/wiki/Causal_analysis

    Causal analysis is the field of experimental design and statistics pertaining to establishing cause and effect. [1] Typically it involves establishing four elements: correlation, sequence in time (that is, causes must occur before their proposed effect), a plausible physical or information-theoretical mechanism for an observed effect to follow from a possible cause, and eliminating the ...

  6. Analysis of covariance - Wikipedia

    en.wikipedia.org/wiki/Analysis_of_covariance

    Analysis of covariance (ANCOVA) is a general linear model that blends ANOVA and regression. ANCOVA evaluates whether the means of a dependent variable (DV) are equal across levels of one or more categorical independent variables (IV) and across one or more continuous variables.

  7. Causal inference - Wikipedia

    en.wikipedia.org/wiki/Causal_inference

    Causal inference is widely studied across all sciences. Several innovations in the development and implementation of methodology designed to determine causality have proliferated in recent decades. Causal inference remains especially difficult where experimentation is difficult or impossible, which is common throughout most sciences.

  8. Blocking (statistics) - Wikipedia

    en.wikipedia.org/wiki/Blocking_(statistics)

    Nuisance variable effect on response variable Nuisance variable (sex) effect on response variable (weight loss) In the examples listed above, a nuisance variable is a variable that is not the primary focus of the study but can affect the outcomes of the experiment. [ 3 ]

  9. Mendelian randomization - Wikipedia

    en.wikipedia.org/wiki/Mendelian_randomization

    The Mendelian randomization method depends on two principles derived from the original work by Gregor Mendel on genetic inheritance. Its foundation come from Mendel’s laws namely 1) the law of segregation in which there is complete segregation of the two allelomorphs in equal number of germ-cells of a heterozygote and 2) separate pairs of allelomorphs segregate independently of one another ...