# dependent variable

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## dependent variable

[di′pen·dənt ′ver·ē·ə·bəl]
(mathematics)
If y is a function of x, that is, if the function assigns a single value of y to each value of x, then y is the dependent variable.

## dependent variable

the measure of the effect of the INDEPENDENT VARIABLE. Thus, in an experiment, or in data analysis, the independent variable (for example, number of years in school) is manipulated, or otherwise controlled, and the effect of this manipulation is seen by the change in the dependent variable (for example, reading proficiency). See also EXPERIMENTAL METHOD.
References in periodicals archive ?
S No###Characteristics###Unit###Constant(a)###Slope (b)###Statistical model for dependent variable in particulate matter [y = a + b(x)]
Multicollinearity occurs when two or more independent variables are highly correlated to each other, making a regression model statistically unreliable because each independent variable is not really explaining anything different about the dependent variable.
The null hypothesis of no serial correlation is rejected for each industry code and dependent variable in our sample.
For identification dependent variable is give support to establishing more private academies, which has two categories (Supporters 0, Non-supporters 1).
Regression between the independent variable (image) and the dependent variable (satisfaction) shows that there was a significant positive correlation between these two variables.
In the latter, we use GRP (both 'physical volume' and deflated values) (9) rather than its growth rate as the dependent variable.
By extrapolation, based on this expression and on other values of independent variables, the corresponding values for the dependent variable are sought.
The model results with the cost of equity as a dependent variable are presented in Table 6.
This significance shows that the variables under study have a significant effect on the dependent variable.
In Model 4, where the dependent variable is the level of real disposable personal income per capita, the Democratic PRESIDENT variable is insignificant, as it was before.
CS, TOEP and AR(1) covariance models were thereby found to be the weakest model in explaining the overall change in the structure of the dependent variable.

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