In a statistical model, you have two kinds of variable. Response variables are the "outputs" of your model. Explanatory variables, on the other hand, are the "inputs" of your model. Response variables are dependent on the explanatory variables. Explanatory variable are independent of the response variables.
Imagine you were trying to formulate a statistical model of your car's fuel economy. The "output" of your model is miles per gallon (or kilometres per litre). That's your response variable. "Inputs" into your model might be (for example) engine capacity, number of cylinders, tyre pressure, etc. These are your explanatory variables. That is, fuel economy may be, or is, (to be determined by the modeling) dependent on engine capacity and/or number of cylinders and/or tyre pressure, etc.
after the treatment
The dependent variable.
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As the explanatory variable increases, the response variable increases
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The dependent variable may change in response to the manipulated variable.
The object upon which the response variable is measured is called experimental. The response variable is the variable whose value can be explained by the predictor variable.
The answer is a dependent variable. A variable that changes in response to another variable is called a dependent variable.
The dependent variable may change in response to the manipulated variable.
The dependent variable.
dependent variable
controlled variable
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responding variable
It is the independent variable that is observed and the dependent that is observed.
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