dependent variable

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Dependent variable

Term used in regression analysis to represent the element or condition that is dependent on values of one or more other independent variables.

Dependent Variable

In technical analysis, a variable whose value is determined by the value of other variable(s), but plays no part in determining the value of those other variable(s). For example, if a product's price is determined by some equation involving the product's supply and its demand, the price is the dependent variable because the price does not affect the supply or demand.

dependent variable

A variable affected by another variable or by a certain event. For example, because a stock's price is affected by dividend payments, earnings projections, interest rates, and many other things, stock price is a dependent variable. Compare independent variable.

dependent variable

a variable that is affected by some other variable in a model. For example, the demand for a product (the dependent variable) will be influenced by its price (the INDEPENDENT VARIABLE). It is conventional to place the dependent variable on the left-hand side of an EQUATION. See DEMAND FUNCTION, SUPPLY FUNCTION.
References in periodicals archive ?
In this study they use firm age as an independent variable and debt as a dependent variable. They check the direct effect of firm age and use of debt.
All analyses were made using the SPSS 16 Statistical Package for correlations and regression analysis for calculating regression coefficients, including regression constants and slopes for dependent variables against the predictor (independent variables).
For the fiscal years 2001 to 2015, we can measure the strength of each of our independent variables to our dependent variable (i.e.
where [y.sub.jit] is the dependent variable, either employment or payroll for a specific NAICS code, i indexes counties, t indexes time, in years, and j indexes either employment or payroll in a particular industry.
In this analysis, we must identify those variables that are strongly correlated with the dependent variable, but superficially correlated among themselves.
Single-subject research studies are classified as having positive, neutral or mixed, or negative effects on the basis of (a) the number and proportion of participants in a study for whom a functional relationship between the independent variable and the dependent variable was established and (b) the direction of the functional relationships.
For the same reason, we will keep the dependent variables in their original units, rather than using log transformations.
The R-Value of the model showed a value of .76 showing that independent variables (internal, external and environmental factors) have a 76% effect on the dependent variable (selection of) which shows that up to 76% of the dependent variable is caused by the independent variables.
Unfortunately, Campbell rejects all means of controlling for those ups and downs that do not involve the use of a dependent variable lagged one or two quarters--a flawed practice for two reasons.
A model with a large regression sum of squares in comparison to the residual sum of squares indicates that the model accounts for most of variation in the dependent variable. Very high residual sum of squares indicate that the model fails to explain a lot of the variation in the dependent variable, and one may want to look for additional factors that help account for a higher proportion of the variation in the dependent variable.
Several dependent variables were explored prior to treatment and following the treatment.