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  2. Dependent and independent variables - Wikipedia

    en.wikipedia.org/wiki/Dependent_and_independent...

    Dependent and independent variables. A variable is considered dependent if it depends on an independent variable. Dependent variables are studied under the supposition or demand that they depend, by some law or rule (e.g., by a mathematical function), on the values of other variables. Independent variables, in turn, are not seen as depending on ...

  3. Causal inference - Wikipedia

    en.wikipedia.org/wiki/Causal_inference

    Causal inference is the process of determining the independent, actual effect of a particular phenomenon that is a component of a larger system. The main difference between causal inference and inference of association is that causal inference analyzes the response of an effect variable when a cause of the effect variable is changed. [1][2] The ...

  4. Regression analysis - Wikipedia

    en.wikipedia.org/wiki/Regression_analysis

    One method conjectured by Good and Hardin is =, where is the sample size, is the number of independent variables and is the number of observations needed to reach the desired precision if the model had only one independent variable. [22] For example, a researcher is building a linear regression model using a dataset that contains 1000 patients ().

  5. Mediation (statistics) - Wikipedia

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

    Simple mediation model. The independent variable causes the mediator variable; the mediator variable causes the dependent variable. In statistics, a mediation model seeks to identify and explain the mechanism or process that underlies an observed relationship between an independent variable and a dependent variable via the inclusion of a third hypothetical variable, known as a mediator ...

  6. Bivariate analysis - Wikipedia

    en.wikipedia.org/wiki/Bivariate_analysis

    Bivariate analysis is one of the simplest forms of quantitative (statistical) analysis. [1] It involves the analysis of two variables (often denoted as X, Y), for the purpose of determining the empirical relationship between them. [1] Bivariate analysis can be helpful in testing simple hypotheses of association.

  7. Design of experiments - Wikipedia

    en.wikipedia.org/wiki/Design_of_experiments

    Design of experiments. The design of experiments (DOE or DOX), also known as experiment design or experimental design, is the design of any task that aims to describe and explain the variation of information under conditions that are hypothesized to reflect the variation. The term is generally associated with experiments in which the design ...

  8. Internal validity - Wikipedia

    en.wikipedia.org/wiki/Internal_validity

    Internal validity. Internal validity is the extent to which a piece of evidence supports a claim about cause and effect, within the context of a particular study. It is one of the most important properties of scientific studies and is an important concept in reasoning about evidence more generally. Internal validity is determined by how well a ...

  9. Controlling for a variable - Wikipedia

    en.wikipedia.org/wiki/Controlling_for_a_variable

    The variables made to remain constant during an experiment are referred to as control variables. For example, if an outdoor experiment were to be conducted to compare how different wing designs of a paper airplane (the independent variable) affect how far it can fly (the dependent variable), one would want to ensure that the experiment is ...