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dependent and independent variables

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concept in mathematical modeling, statistical modeling and experimental sciences
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There may be a demonstrable relationship and a positive correlation between dependent and independent variables.
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Control variables could strongly influences experimental results, were they not held constant during the experiment in order to test the relative relationship of the dependent and independent variables.
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d) Hedonic regression models should use the logarithm of price as the dependent variable, and preferably also logarithms of the independent variables- regressions that are linear in raw variables are to be avoided
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In a binary regression model with a logit link function, we used self-rated poor health as the binary dependent variable, and age, sex and education as the independent variables.
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The sign of the Spearman correlation indicates the direction of association between X (the independent variable) and Y (the dependent variable).
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Discriminant analysis is also different from factor analysis in that it is not an interdependence technique: a distinction between independent variables and dependent variables (also called criterion variables) must be made.
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In statistics, polynomial regression is a form of regression analysis in which the relationship between the independent variable x and the dependent variable y is modelled as an nth degree polynomial in x.
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Furthermore, a Box-Behnken design was constructed for the SFE technique using pressure, temperature, and particle size as independent variables, and yields of crude extract, individual and total secondary metabolites as the dependent variables.
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Multiple linear regression is a generalization of simple linear regression to the case of more than one independent variable, and a special case of general linear models, restricted to one dependent variable.
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Three economic experts said that both estimates were possible, but they depended on unknown variables such as the division of UK government debt, future North Sea oil revenues, possible spending commitments of an independent Scotland and future productivity gains.
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He worked on the general theory of functions, studying relationships between independent and dependent variables.
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If investigating dependence, set the independent variable on the x-axis and the dependent variable on the y-axis.
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Regression Analysis is a technique used for the modeling and analysis of numerical data consisting of values of a dependent variable (response variable) and of one or more independent variables (explanatory variables).
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TFR is the dependent variable, while the logarithm of population density and year dummies are independent variables.
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Regression Analysis is a statistical forecasting method, that is concerned with describing and evaluating the relationship between a particular dependent variable and one or more other variables (usually called the independent variables).
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The dependent variable in the regression equation is modeled as a function of the independent variables, corresponding parameters ("constants"), and an error term.
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A common goal for a statistical research project is to investigate causality , and in particular to draw a conclusion on the effect of changes in the values of predictors or independent variables on dependent variables .
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