dependent variable

(redirected from Dependent variables)
Also found in: Dictionary, Thesaurus, Financial, Encyclopedia.

variable

[var´e-ah-b'l]
something that changes; an attribute or property of a person, event, or object that is known to vary in a given study.
dependent variable in a mathematical equation or relationship between two or more variables, a variable whose value depends on those of others; it represents a response, behavior, or outcome that the researcher wishes to predict or explain.
extraneous variable a factor that is not itself under study but affects the measurement of the study variables or the examination of their relationships.
independent variable in a mathematical equation or relationship between two or more variables, any variable whose value determines that of others; it represents the treatment or experimental variable that is manipulated by the researcher to create an effect on the dependent variable.

de·pen·dent var·i·a·ble

in experiments, a variable that is influenced by or dependent on changes in the independent variable; for example, the amount of a written passage retained (dependent variable) as a function of the different numbers of minutes (independent variable) allowed to study the passage.

dependent variable

(in research) a factor that is measured to learn the effect of one or more independent variables. For example, in a study of the effect of preoperative nursing intervention on postoperative vomiting, vomiting is the dependent variable measured to determine the effect of the nursing intervention. Compare independent variable.

dependent variable

An objective finding measured in an experiment that is expected to change as a result of an experimental manipulation of the independent variable(s).

dependent variable

Epidemiology An outcome variable/variables that reflects other, independent, variables in the relationship being studied. See Variable.

variable

1. any type of measurement, quantitative or qualitative, of which a series of individual observations is made so that it has, as a principal characteristic, the potential for variability.
2. has the quality of variability.

variable agent
an agent in the cause of a disease which is capable of variation in intensity, e.g. weather, as contrasted to one that is not variable, e.g. Salmonella dublin.
concomitant v's
in experimental design these refer to factors that affect the dependent variable, but are not themselves influenced by the treatment (e.g. age of animal). The effect of concomitant variables can be removed by suitable experimental design or by including them in the model.
continuous variable
one in which all values within a given range are possible, e.g. birth weights of calves.
variable costs
costs which vary with the dimensions of the activity. Includes seed, fertilizer, teat dip, worm drench. Called also direct costs. See also fixed costs.
dependent variable
1. in statistics the variable predicted by a regression equation.
2. a variable which depends on other variables for its value.
discontinuous variable
see discrete variable (below).
discrete variable
one in which the possible values are not on a continuous scale, e.g. the number of sheep in a flock.
endogenous variable
dependent variable.
exogenous variable
independent or predetermined variable.
independent variable
one not dependent on other variables but capable of affecting dependent variables, thus an input variable.
spatial variable
a measurement relating to area or location.
temporal variable
one relating to chronological time.
References in periodicals archive ?
In this study, R2 value for SO 2- and electrical conductivity are only 24%, but their ANOVA results are significant and hence only 24% explained variation cannot be neglected and can be considered for estimation of the dependent variables.
05 is considered significant for predicting the dependent variable.
This was performed separately for each industry code and each dependent variable in our dataset.
For identification dependent variable is give support to establishing more private academies, which has two categories (Supporters 0, Non-supporters 1).
In this analysis, we must identify those variables that are strongly correlated with the dependent variable, but superficially correlated among themselves.
The independent variables have a 76% effect on the dependent variable as shown by the R value of .
And why should anyone estimate these equivalent models in the form of his Model 2, which includes a lagged dependent variable that merely disguises the dependence of [[?
15)-(18) include 4 dependent variables (metabolite concentrations), 12 independent variables (maximum reaction rates), 8 rate constants for both incoming and outgoing fluxes and 19 kinetic orders for incoming and 20 kinetic orders for outgoing fluxes.
3 provides a variety of measures assessing the success of the model in predicting the dependent variable.
Then, we read horizontally from the line of best fit to the y-axis to see the expected value for the dependent variable (follow the dotted line in Figure 1).
In this case, using a multinomial logit model (2) does not consider the fact that the dependent variable reflects an order.
We were specifically looking for patterns (correlations) between fourteen Dependent Variables and six Independent Variables (see Table A).

Site: Follow: Share:
Open / Close