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  2. Moderation (statistics) - Wikipedia

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

    The third variable is referred to as the moderator variable (or effect modifier) or simply the moderator (or modifier). [1] [2] The effect of a moderating variable is characterized statistically as an interaction; [1] that is, a categorical (e.g., sex, ethnicity, class) or continuous (e.g., age, level of reward) variable that is associated with ...

  3. Confounding - Wikipedia

    en.wikipedia.org/wiki/Confounding

    Confounding is defined in terms of the data generating model. Let X be some independent variable, and Y some dependent variable.To estimate the effect of X on Y, the statistician must suppress the effects of extraneous variables that influence both X and Y.

  4. Spurious relationship - Wikipedia

    en.wikipedia.org/wiki/Spurious_relationship

    Graphical model: Whereas a mediator is a factor in the causal chain (top), a confounder is a spurious factor incorrectly implying causation (bottom). In statistics, a spurious relationship or spurious correlation [1] [2] is a mathematical relationship in which two or more events or variables are associated but not causally related, due to either coincidence or the presence of a certain third ...

  5. Glossary of experimental design - Wikipedia

    en.wikipedia.org/wiki/Glossary_of_experimental...

    Effect (of a factor): How changing the settings of a factor changes the response. The effect of a single factor is also called a main effect. A treatment effect may be assumed to be the same for each experimental unit, by the assumption of treatment-unit additivity; more generally, the treatment effect may be the average effect.

  6. Controlling for a variable - Wikipedia

    en.wikipedia.org/wiki/Controlling_for_a_variable

    This is typically done so that the variable can no longer act as a confounder in, for example, an observational study or experiment. When estimating the effect of explanatory variables on an outcome by regression, controlled-for variables are included as inputs in order to separate their effects from the explanatory variables. [1]

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    mail.aol.com

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  8. Executive Orders Signed By Donald Trump - The Huffington Post

    data.huffingtonpost.com/2017/trump-executive-orders

    President Donald Trump signed 32 executive orders in his first 100 days.. Presidential usage of executive orders has varied wildly throughout history. George Washington issued eight.

  9. Correlation does not imply causation - Wikipedia

    en.wikipedia.org/wiki/Correlation_does_not_imply...

    Example 3. In other cases it may simply be unclear which is the cause and which is the effect. For example: Children that watch a lot of TV are the most violent. Clearly, TV makes children more violent. This could easily be the other way round; that is, violent children like watching more TV than less violent ones. Example 4