Research variables types characteristics and examples
Research variables are the different characteristics or properties of living beings, objects or phenomena that have the particularity of undergoing changes and that can be observed, measured, analyzed and controlled during the process of an investigation.
Some examples of variables are a population’s socioeconomic status, place of residence, political preferences, education level, gender, age, radiation level, ambient temperature, or levels of polluting gases.
A variable is a property of the object of study that can take on two or more values (that is, it can change). Therefore, if this does not happen, the observed characteristic is not a variable, but a constant.
For example, an investigation wants to know how solar radiation levels (independent variable) affect the growth of a plant (dependent variable). As you can see, both variables can have two or more values, and it is expected that as one changes (solar radiation), the other changes (plant growth).
The definition of variables
One of the most important steps in scientific research is the definition of variables. This is because it is not possible to do an investigation without specifying and strictly defining the variables to be studied.
The definition of variables in scientific research is one of the most complicated tasks that the researcher must perform. This process must be carried out very rigorously, because only in this way will the researcher achieve the established objectives.
The researcher specifies the study variable and determines how it will be measured or evaluated. Once this process is completed, data collection instruments are developed.
Some examples of variable definition:
-And father : the time in years elapsed from birth to the date of the interview.
– Origin : place where the interviewee or patient resides.
– Fever: finding of body temperature (axillary) greater than or equal to 38 degrees Celsius (ºC).
– Degree of dehydration of an individual : refers to fluid loss, which according to the clinical scale can be mild, moderate or severe.
Classification of search variables
– Types of variables according to their nature
Depending on their nature, variables are classified as qualitative or quantitative.
It is these variables that can be measured or counted. For example, the number of inhabitants in a region or the number of people in a theater.
In addition, quantitative variables are classified as continuous and discrete.
- Continuous variables : are those that can take on fractional or decimal values. For example, the degree of human body temperature, which can be 37°C or 37.5°C.
- Discrete variables: are those that receive integer values. For example, the number of people in a theater can be 100, but it will never be 100.5 people.
These are the variables that represent an attribute of the individual or object in question, therefore, their representation is not numerical. For example: the gender or type of diet of a group of children.
Qualitative variables differentiate two or more aspects of the object of study and can be dichotomous and polychotomous.
- Dichotomous variables: are those that express two possibilities for the studied characteristic. Examples: gender (female or male), types of schools (public or private).
- Polychotomous variables: manifest more than two characteristics. Example: the socioeconomic stratum of a population, which can move from class 1 to class 5.
– Types of variables according to their complexity
Depending on the degree of complexity, variables are classified as simple or complex:
These are variables that are expressed directly through a number or a quality. For example, gender manifests itself in two ways: masculine or feminine; age is expressed in years that have been completed.
These variables are initially decomposed or divided into several generalities, because they cannot be studied as a whole; therefore, each part is defined individually. These will be exemplified in the examples section.
– Variable types according to their function or relationship
Depending on their relationship to other characteristics of the object of study, the variables can be independent, dependent, intervening or confounding.
They are the ones that cause changes in other variables. Independent variables are used or manipulated by the researcher to explain the observed phenomenon. Example: the type of exercises a therapist subjects patients to see its impact on obesity.
These are the variables modified by the action of the independent variable. They are the ones who measure and originate the research results. Example: the patients’ body weight after performing the indicated exercises for a certain time.
Stakeholders or mediators
These variables are between the independent variable and the dependent variable and can interfere with the response of the latter. They must be identified and controlled so that the results obtained come from the independent variable. For example: the type of food ingested by patients who perform the exercises.
confused or strange
These variables affect both dependent and independent variables. For example, hereditary factors that affect the body weight of people who exercise.
– Types of variables according to the measurement level
Variables in this category are classified into ordinal, nominal, range, and ratio.
In these variables, an order is established in the values or characteristics that they define. Example: a student’s grades or grades, which are established from lowest to highest score; or the level of schooling, which can be established from basic education to university.
As can be seen, in this type of variables, the values or properties indicate hierarchies. Therefore, when numbers are used, the values are not arbitrary, but represent the order of the observed attribute.
In these variables, the elements that compose them are classified into categories that follow an order or degree. In this way, the differences between two consecutive values do not vary, that is, they are established at equal intervals.
Likewise, the value zero in this case is considered a reference value, but does not indicate the absence of the attribute.
For example, the height of mountains taking sea level as a reference. In this case, the zero value assigned to the sea is arbitrary.
These variables have both ordinal and range properties. But in this category the zero value is real and represents the absence of the characteristic. For example, the number of children in a family. In this case, the value “zero children” would indicate the absence of children.
Examples of search variables
– Continuous Quantitative : Measures people’s weight in kilograms, which can be a whole number, such as 50 kilograms, or a fraction, such as 55.5 kilograms.
– Discrete Quantitative : The number of students in a class, which will always be an integer, such as 50 or 100.
– Qualitative dichotomous : the types of vehicles. This variable can be divided, for example, into two varieties: racing cars and touring cars.
– Polychotomous qualitative: the degree of dehydration of a person, which can be mild, moderate or severe.
-Simple : eye color (black, blue, brown) or favorite ice cream flavor (strawberry, vanilla, butter).
-Complex : an example of the use of these variables is the evaluation of the quality of service provided by a place that sells food and has a small restaurant.
In this case, the variable is the quality of service at all facilities. But, as it is very broad, it is divided according to the main areas that pay attention to the public.
In this example, you can define the divisions of the variable and the ways in which they will be measured:
-Quality of service in the area of sales of sweets and ice cream: responsibility and courteous treatment will be evaluated.
-Quality of service in the restaurant area: the quality of the food and the speed of service will be evaluated.
-Quality of service in the delicatessen sales area: evaluation and cleanliness and friendly treatment will be evaluated.
-Independent, dependent, intervening or confusing variables
A teacher applies a new mathematics learning methodology to a group of students to increase interest in this science.
In this example, the independent variable (VI) is the learning technique applied and the dependent variable (DV) is the student’s increased interest in mathematics; while the intervening variable can be the excess of tasks in other subjects or the possible existence of cognitive factors that impair learning in certain students.
Ordinals: examples of this variable are the different ranks of university professors or the degrees of the military career. In both cases, an order is established.
-Intervals: an example of this variable is the measurement of the ambient temperature in ºC. 0ºC is included in this measurement scale, which does not indicate the absence of temperature, as this value is considered more of a reference value.
The values in this example can go from positive to negative, for example: 24ºC can pass through the 0ºC value and reach negative values like -20ºC.
Ratio : Examples of these variables are measures of income or output. A family group can make an investment of 400,000 currency units and have an income of 450,000, which would imply a profit of 50,000 currency units.
Furthermore, in these variables there is an absolute zero, since a family can also have an income equal to the investment, the profit being equal to zero currency units.