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  2. Multivariate statistics - Wikipedia

    en.wikipedia.org/wiki/Multivariate_statistics

    Multivariate statistics is a subdivision of statistics encompassing the simultaneous observation and analysis of more than one outcome variable, i.e., multivariate random variables. Multivariate statistics concerns understanding the different aims and background of each of the different forms of multivariate analysis, and how they relate to ...

  3. Response surface methodology - Wikipedia

    en.wikipedia.org/wiki/Response_surface_methodology

    In statistics, response surface methodology (RSM) explores the relationships between several explanatory variables and one or more response variables. RSM is an empirical model which employs the use of mathematical and statistical techniques to relate input variables, otherwise known as factors, to the response.

  4. Beneish M-score - Wikipedia

    en.wikipedia.org/wiki/Beneish_M-Score

    Beneish M-score is a probabilistic model, so it cannot detect companies that manipulate their earnings with 100% accuracy. Financial institutions were excluded from the sample in Beneish paper when calculating M-score since these institutions make money through different routes.

  5. Interaction (statistics) - Wikipedia

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

    Interaction effect of education and ideology on concern about sea level rise. In statistics, an interaction may arise when considering the relationship among three or more variables, and describes a situation in which the effect of one causal variable on an outcome depends on the state of a second causal variable (that is, when effects of the two causes are not additive).

  6. Coefficient of multiple correlation - Wikipedia

    en.wikipedia.org/wiki/Coefficient_of_multiple...

    The coefficient of multiple correlation is known as the square root of the coefficient of determination, but under the particular assumptions that an intercept is included and that the best possible linear predictors are used, whereas the coefficient of determination is defined for more general cases, including those of nonlinear prediction and those in which the predicted values have not been ...

  7. Dummy variable (statistics) - Wikipedia

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

    The variable could take on a value of 1 for males and 0 for females (or vice versa). In machine learning this is known as one-hot encoding. Dummy variables are commonly used in regression analysis to represent categorical variables that have more than two levels, such as education level or occupation.

  8. Variable and attribute (research) - Wikipedia

    en.wikipedia.org/wiki/Variable_and_attribute...

    The values are ordered in a logical way and must be defined for each variable. Domains can be bigger or smaller. The smallest possible domains have those variables that can only have two values, also called binary (or dichotomous) variables. Bigger domains have non-dichotomous variables and the ones with a higher level of measurement.

  9. Triple product rule - Wikipedia

    en.wikipedia.org/wiki/Triple_product_rule

    Suppose a function f(x, y, z) = 0, where x, y, and z are functions of each other. Write the total differentials of the variables = + = + Substitute dy into dx = [() + ()] + By using the chain rule one can show the coefficient of dx on the right hand side is equal to one, thus the coefficient of dz must be zero () + = Subtracting the second term and multiplying by its inverse gives the triple ...