Independent Variable Definition and Examples

Independent Variable Definition and Examples The two main variables in a science experiment are the independent variable and the dependent variable. Heres the definition on independent variable and a look at how its used: Key Takeaways: Independent Variable The independent variable is the factor that you purposely change or control in order to see what effect it has.The variable that responds to the change in the independent variable is called the dependent variable. It depends on the independent variable.The independent variable is graphed on the x-axis. Independent Variable Definition An independent variable is defines as the variable that is changed or controlled in a scientific experiment. It represents the cause or reason for an outcome.Independent variables are the variables that the experimenter changes to test their dependent variable. A change in the independent variable directly causes a change in the dependent variable. The effect on the dependent variable is measured and recorded. Common Misspellings: independant variable Independent Variable Examples A scientist is testing the effect of light and dark on the behavior of moths by turning a light on and off. The independent variable is the amount of light and the moths reaction is the dependent variable.In a study to determine the effect of temperature on plant pigmentation, the independent variable (cause) is the temperature, while the amount of pigment or color is the dependent variable (the effect). Graphing the Independent Variable When graphing data for an experiment, the independent variable is plotted on the x-axis, while the dependent variable is recorded on the y-axis. An easy way to keep the two variables straight is to use the acronym DRY MIX, which stands for: Dependent variable that Responds to change goes on the Y axisManipulated or Independent variable goes on the X axis Sources Dodge, Y. (2003). The Oxford Dictionary of Statistical Terms. OUP. ISBN 0-19-920613-9.Everitt, B. S. (2002). The Cambridge Dictionary of Statistics (2nd ed.). Cambridge UP. ISBN 0-521-81099-X.Gujarati, Damodar N.; Porter, Dawn C. (2009). Terminology and Notation. Basic Econometrics (5th international ed.). New York: McGraw-Hill. p. 21. ISBN 978-007-127625-2.