Types of Research Variables
Contents
According to Winarno (2013), the types of variables are differentiated based on their position in a study. In a study that studies causal relationships between variables, several types of variables can be identified, namely: dependent variable, independent variable, moderator variable, control variable, and intermediate or intervening variable. The relationship between these variables in the study is shown in the diagram below.
Research variables are objects that become the focus of a study. The research variables consisted of dependent variables, independent variables, moderator variables, control variables, and intermediate or intervening variables. The explanation of each research variable is as follows:

Dependent variable
The dependent variable is the response or output variable. The dependent or dependent variable or called the output variable, the criteria, the consequence, is the variable that is affected or the result, because of the independent variable. The dependent variable is not manipulated, but the variation is observed as a result that is predicted to come from the independent variable. Usually the dependent variable is the condition we want to describe. In experiments, the independent variable is the variable that is manipulated/played by the experimenter.
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For example, in a study of the relationship between the following two variables: (1) The relationship between leg muscle strength (X) and the distance a soccer player kicks (Y), (2) The relationship between arm muscle strength (X) and the accuracy of a volleyball player’s serve ( Y). Starting from the two examples above, the researcher asks: what will happen to Y if X is made larger or smaller? In this case the researcher views Y as the dependent variable, because Y will change as a result of changing X. It is called dependent because the value of Y will change (bound/dependent) on the value of the independent variable (X).

Independent Variable
The independent variable is the variable that is suspected to be the cause of the emergence of the dependent variable. Independent variables are often referred to as stimulus, predictor, and antecedent variables. The independent variable is the variable that affects or is the cause of the change or emergence of the dependent variable. Independent variables are usually manipulated, observed, and measured to determine their relationship (influence) with other variables.
For example, in a study of the relationship between the following two variables: (1) The relationship between leg muscle strength (X) and the distance a soccer player kicks (Y), (2) The relationship between arm muscle strength (X) and the accuracy of a volleyball player’s serve ( Y). Starting from the two examples above, the researcher asks: what will happen to Y if X is made larger or smaller? In this case the researcher views Y as the dependent variable, because Y will change as a result of changing X. It is called dependent because the value of Y will change (bound/dependent) on the value of the independent variable (X).

Moderator Variables
The moderator variable is an intermediate variable, it is a special type of independent variable, namely the secondary independent variable which is appointed to determine whether it affects the relationship between the primary independent variable and the dependent variable. The moderator variable is the factor that is measured, manipulated or chosen by the researcher to reveal whether the factor changes the relationship between the independent variable and the dependent variable. If the researcher wants to study the effect of the independent variable X on the dependent variable Y but is unsure whether the relationship between X and Y changes due to variable Z, then Z can be analyzed as a moderating variable.
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Control Variable
Not all variables in a study can be studied at the same time. Some of these variables must be neutralized to ensure that the variables in question do not interfere with the relationship between the independent variable and the dependent variable. The variables whose influence must be neutralized are referred to as control variables. So, control variables are factors whose influence is controlled or neutralized by the researcher because if they are not neutralized, they are thought to have influenced the relationship between the independent variable and the dependent variable. The control variable is different from the moderator variable. The determination of a variable to be a moderating variable is to study (analyze) its effect, while the determination of a control variable is to neutralize/equalize its effect.

Intervening Variables (Intervening)
The description of the variables above are concrete (real) variables. The independent variables, moderator variables, and control variables can be manipulated by researchers and can be observed (measured) their effect on the dependent variable. If a variable that you want to know its effect on the dependent variable turns out to be unobservable (measured) because it is too abstract, then the variable is usually viewed as an intervening variable. So the intermediate variable is a factor that theoretically has an influence on the dependent variable but cannot be seen so that it cannot be measured or manipulated. The effect of the intervening variable on the dependent variable can only be inferred based on the effect of the independent variable and/or the moderator variable on the dependent variable.
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Discrete Variable
Discrete variables: also called nominal variables or categorical variables because they can only be categorized into two opposite poles, namely “yes” and “no”. For example yes women, no women, or in other words: “womenmen”, “presentabsence”, “topdown”. Numbers are used in this discrete variable which can be operated to calculate the frequency of occurrences, i.e. number of men, number of attendance and so on. Then the number is expressed as a frequency. Thus research data with discrete variables is a categorical marker, which cannot be operated in the form of addition, subtraction, multiplication or division. Its existence is limited to determination as frequency.

Continuous Variable
Continuum variables can be separated into three types of small variables, namely:
 Ordinal variables, namely variables that show the order based on levels, for example very high, tall, short. Another term is the “more or less” variable because one has advantages over the other. Example: Agung is smart, Nico is smart, Ganang is not smart.
 Interval variables, namely variables that have a distance, when compared to other variables, while the distance itself can be known with certainty. For example: The air temperature outside is 31 ° C. Our body temperature is 37 ° C. So the difference in temperature is 6 ° C. The distance from Surabaya to Blitar is 162 km, while SurabayaMalang is 82 km. Then the difference between MalangBlitar distance, which is 80 km.
 The ratio variable, namely the comparison variable. The ratio variable has an absolute zero value that can be operated in the form of multiplication many times. Example: Mr. Rudi’s weight is 70 kg, while his son is 35 kg. So Mr. Rudi weighs twice as much as his son.
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