independent variable

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Independent variable

Term used in regression analysis to represent the element or condition that is expected to influence another (so-called dependent) variable.

Independent Variable

In technical analysis, a variable whose value is not determined by the value of other variable(s), but rather determines 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, supply and demand are independent variables because together they determine the product's price. See also: Dependent variable.

independent variable

A variable that is not affected by any other variables with which it is compared. For example, in comparing the price of an electric utility stock with interest rates, the interest rates are an independent variable because they are not affected by utility stock prices. Compare dependent variable.

independent variable

a variable that affects some other variable in a model. For example, the price of a product (the independent variable) will influence the demand for it (the DEPENDENT VARIABLE). It is conventional to place the independent variable on the right-hand side of an EQUATION. See DEMAND FUNCTION, SUPPLY FUNCTION.
References in periodicals archive ?
Demonstration of a functional relationship is compromised when (a) there is a long latency between manipulation of the independent variable and change in the dependent variable, (b) mean changes across conditions are small and/or similar to changes within conditions, and (c) trends do not conform to those predicted following introduction or manipulation of the independent variable.
A predicted logit for case i is obtained from the solved logistic regression equation by substituting the case's values of the independent variables into the sample estimate of the logistics regression equation,
Concurvity in the data for a spatial GAM can lead to bias in the fitted linear parameter; this bias, if it occurs, probably depends on complex interrelationships among the independent variables.
Moreover, the independent variables in a well-specified model will be statistically significant at some acceptable level of confidence.
The summary output for a regression model in Excel yields a great amount of statistical information, and within that, it's Intuitively, one would think there would be a descending strength of correlation from net outlays to the independent variables since each phase of the PPBE builds upon the one that precedes it.
Among the various available statistics Cox and Snell R2 and Nagelkerke are mostly used to asses the goodness-of-fit of the model with all of the independent variables and told us magnitude of the explained variation.
In case of direct causal effect of leadership styles on the dependent variable, job satisfaction, the significant path coefficients for H12, H13, H14, and H15 affirmed that all four independent variables have direct effect on the level of job satisfaction.
It is widely used to predict the probability of the presence or absence of a disease, success or failure, or an outcome generally based on discrete, continuous, or categorical independent variables.
The purpose of multiple regression (a term used by Pearson, 1908) is to highlight the relation between a dependent variable (explained, endogenous or resultant variables) and a lot of independent variables (explanatory, factor, exogenous, predictor ones).
The second output of 4-4 chart represents the correlation coefficient between (SEASON, DISP, OPLEV,STICKY, DOWN, VSALE, MV, LOSS) as independent variables and (ABS-FE) as a dependent variable = 0.
The responses were later tabulated and analyzed using regression analysis to understand the effect of the independent variables on the dependent variables.
The first model contained two independent variables such as bond value and profit, and the second model assumed only dividend as independent variable.

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