Last Updated on September 18, 2020 by Sagar Aryal
Independent Variables
The Independent variable is a type of variable used in experimental sciences, statistical modeling, and mathematical modeling which doesn’t depend on any other variables in the scope of the experiment.
 An independent variable can be manipulated in an experiment, which in turn affects the changes in the dependent variables.
 Mostly in mathematical equations, independent variables are denoted by ‘x’.
 Independent variables are also termed as “explanatory variables,” “manipulated variables,” or “controlled variables.”
 In a graph, the independent variable is usually plotted on the Xaxis.
 Independent variables are mostly used in experiments to determine their effects on other dependent variables.
 However, in other cases where their influence is not of primary importance, they are used to account for their potential confounding effect.
 The concept of independent variables might differ from one sector to another. In statistics, independent variables are those that are manipulated by the experimenter.
 In research, independent variables are the variables that are selected to determine their possible effects on other variables being studied.
 Independent variables are required for the existence or study of any dependent variable. Also, one independent variable might affect two different dependent variables.
 These variables are used in experiments to study the causeeffect relationship where changes in independent variables make up the ‘cause’ part of the experiment.
 Examples of independent variables depend on the nature of the experiment, and some of these variables with experiments are:
 In an experiment testing the behavior of moths to light and dark by turning the light on and off, the light is the independent variable.
 In a study determining the effects of temperature on the plant pigmentation, the temperature is the independent variable.
Dependent variables
The dependent variable is a type of variable used in experimental sciences, statistical modeling, and mathematical modeling which depends on any other variables in the scope of the experiment.
 A dependent variable cannot be manipulated by the experimenter as the changes are brought by the independent variables.
 Mostly in mathematical equations, dependent variables are denoted by ‘y’.
 Dependent variables are also termed as “measured variable,” the “responding variable,” or the “explained variable”.
 In a graph, dependent variables are usually plotted on the Yaxis.
 Dependent variables are used in experiments to study their values under the supposition or hypothesis that they depend on, by some law or rule, on other variables, called independent variables.
 Most experiments are involved in the observation of changes or variations in the dependent variables.
 The concept of dependent variables might also differ from one sector to another. In statistics, dependent variables are those that are expected to change when the independent variables are manipulated.
 A dependent variable responds to the one or many independent variables and thus, ‘depends’ on those variables.
 Dependent variables cannot exist without independent variables, and one dependent variable can only be affected by one independent variable during one study.
 These variables are used in experiments to study the causeeffect relationship where changes in dependent variables caused due to independent variables make up the ‘effect’ part of the experiment.
 The effect on the dependent variable forms the basis of any experiment.
 Examples of dependent variables depend on the nature of the experiment, and some of these variables with experiments are:
 In an experiment testing the behavior of moths to light and dark by turning the light on and off, the behavior of moths towards the light is the dependent variable.
 In a study determining the effects of temperature on the plant pigmentation, the changes in plant pigmentation as a response to temperature is the dependent variable.
Key Differences (Independent variable vs Dependent variables)
Basis for Comparison  Independent variable  Dependent variables 
Definition  The Independent variable is a type of variable used in experimental sciences, statistical modeling, and mathematical modeling which doesn’t depend on any other variables in the scope of the experiment.  The dependent variable is a type of variable used in experimental sciences, statistical modeling, and mathematical modeling which depends on any other variables in the scope of the experiment. 
Also called  Independent variables are also termed as “explanatory variables,” “manipulated variables,” or “controlled variables.”  Dependent variables are also termed as “measured variable,” the “responding variable,” or the “explained variable”. 
Denoted by  In mathematical equations, independent variables are denoted by ‘x’.  In mathematical equations, dependent variables are denoted by ‘y’. 
Graph  In a graph, the independent variable is usually plotted on the Xaxis.  In a graph, dependent variables are usually plotted on the Yaxis. 
Dependence  As the name suggests, independent variables of an experiment do not depend on other variables.  As the name suggests, the dependent variables of an experiment depend on independent variables. 
Changes caused by  The changes in the independent variables are brought about by the experimenter.  The changes in the dependent variables are brought about by the changes in the independent variables. 
Causeeffect  Changes in independent variables make up the ‘cause’ part of the experiment.  Changes in dependent variables caused due to independent variables make up the ‘effect’ part of the experiment. 
Existence  Independent variables can exist without dependent variables.  Dependent variables cannot exist without independent variables. 
Attributes  Independent variables take the form of experiment stimulus having two attributes that are either present or absent.  Dependent variables have attributes that are direct, indirect, or through constructs. 
Examples 


Examples of independent variables
Nonliving variables
 In experiments, it is easier to implement nonliving independent variables as the manipulation of such variables is easier.
 Examples of independent variables can be studied in a study testing two different smoothing processes on four different brands of dental cement.
 In the study mentioned above, the independent variables can be the application method and materials, lightcuring intensities on the cement, specimen storage (temperature and duration), the length of time of the polishing process, the settings of the electron microscope, and the rotation speed of the polishing device.
 The result of changes in any one of these variables on the process is the basis for this experiment.
Living variables
 Living variables are much complex and thus more challenging to control.
 Due to these reasons, most experiments use simpler organisms like microbes, insects, and rats to generate the results.
 These experiments are only used on human samples once all the results from the study on simpler animals are obtained.
 It is also important to limit other variables not being studied as they might cause changes in independent and dependent variables.
 Some common independent variables in living systems include age group, gender, or body mass index.
Examples of dependent variables
Recovery of patients
 In a study to determine the effectiveness of drugs on the recovery of patients suffering from cold, the rate of recovery of the patients is the dependent variable.
 Here, half of the patients are given the drugs while the rest are not. Then, the rate of recovery of the patients taking the drugs and those not taking the drugs are observed.
 If the rate of recovery in patients taking the drug is higher than those not taking the drugs, the drug is deemed effective.
 However, if the rates of recovery are the same in both cases, the drug is deemed ineffective against the cold.
Changes in plant pigmentation with temperature
 In another study conducted to determine the effect of temperature on plant pigmentation, the changes in plant pigmentation with changes in temperature is the dependent variable.
 The study is conducted while changing the temperature of the environment, and the changes in pigmentation on the plants is observed and noted down.
 Based on this, the effect of temperature on plant pigmentation can be determined.
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