por A qualitative variable, also called categorical variable, is the one that takes a characteristic into consideration. Its function is the expression of qualities or peculiarities of people, objects or situations that do not have a numerical character.
In general, they are non-numeric variables. For example, hair color, nationality, cat breeds, city of residence, clothing brand, university, colors, names, religion, political parties, professions…
Let’s take the example of an investigation; You want to investigate how the city you live in (qualitative independent variable) influences the religion you profess (qualitative dependent variable).
This type of variable allows those elements that are not numeric to be expressed in the statistical field. As they are about qualities and not numbers, the results of research that include qualitative variables are usually of a general and non-specific nature.
Despite not being numerical, qualitative variables can also be used in purely financial or economic fields; in these cases each category assumes a number that identifies it.
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Characteristics
– Qualitative variables are characterized by not being numerical. Rather, they consider qualities and characteristics that are relevant in a specific context.
– The qualities considered as qualitative variables have a place within a particular category. For example, they can be colors, names of people, cities, countries, among others.
– They are finite. This characteristic is common to all types of variables, since a certain number of values that are relevant to the particular subject to be investigated are always considered.
– Since they encompass qualities and characteristics, qualitative variables are divided into various types according to the nature of said specific quality. They can be nominal, ordinal, or binary.
– Sometimes qualitative variables can be assigned numbers. This is intended to facilitate a more reliable statistical analysis.
Guys
Qualitative variables can be divided according to several criteria. Below we will describe the main categories:
– According to the number of values considered
dichotomous
Dichotomous qualitative variables can only consider two values. Examples of this are sex (male or female), or affirmation or denial.
polytomous
These variables are characterized because they contemplate three or more values. Within these can be found scales that imply a certain order (such as: good, regular, bad) or scales that have no associated order (for example, colors).
– Depending on the nature of the variable
binary
Binary qualitative variables consider two values, to which numbers (0 or 1) are assigned. This type of variable is widely used in the economic, financial, statistical and biological fields.
The values taken into account as binary qualitative variables must be exhaustive. In other words, the options chosen must cover all the possibilities that can be generated related to said values.
Likewise, the values must be mutually exclusive; that is, one option must cancel the other, the fact that a certain value is given makes it impossible for another to be given.
Thanks to this type of variables, it is possible to carry out statistical analyzes of more complex scenarios without having advanced mathematical knowledge. They are very useful when solving problems in which the main factors to consider are not numerical values, but other types of qualities.
Nominal
This type of qualitative variables does not respond to any specific order. The values that make up this category are not governed by ordinal scales; rather they correspond to characteristics with a high degree of independence in relation to each other.
Nominal variables are considered to have less mathematical precision; for this reason, they are less used in these areas.
Ordinal
Ordinal variables are those that do imply a scale of order; that is, they are subject to ordinal criteria. They are also known as quasi-quantitative variables.
The values that make up this category must conform to a specific classification. Likewise, the intervals that exist between one value and another may not be uniform, but there must always be an order relationship.
Examples of qualitative variables
– The fear
This is a nominal qualitative variable, since it cannot be measured numerically. Fear is a variable that changes according to the person who feels it and fluctuates depending on the situation in which they feel when reacting to a certain event or event.
– Hunger
Hunger cannot be measured numerically, therefore, it is considered as an ordinal qualitative variable. This variable can only be perceived by the person who feels it and can be classified as a lot, a little or not at all, depending on the situation or specific time.
– The beauty
This variable is a concept that can only be measured by the individual who interprets it. Beauty is a quality that lacks numerical value and cannot be classified within a scale. Therefore, it is a nominal qualitative variable.
– Civil status
A person’s marital status is a nominal qualitative variable that cannot be assigned a numerical value. It is a concept that does not have a specific established order.
– The happiness
This variable cannot be measured numerically as it depends on the value that each person assigns to it. Happiness is a property that each individual feels subjectively and there is no tool to measure the degree of happiness that a person can feel.
– The ignorance
This variable cannot be measured numerically and is expressed in attitudes and specific moments.
– Utility
The variable that determines how useful an object is is purely qualitative. In this way, utility is perceived by each individual according to a specific situation.
– The type of medal
This is an ordinal qualitative variable, since there is a classification by categories that assigns a place within a competence. In this way the gold, silver and bronze medals denote the place occupied in a competition without the need to assign a numerical value to the results.
– The creativity
This variable is qualitative since creativity cannot be measured numerically. In the same way, it is a factor that varies from person to person depending on the specific moment in which it takes place.
– The grade of an exam
When an exam is graded with the terms passed, outstanding, acceptable or deficient, it is an ordinal qualitative variable, since a numerical value is not being assigned to the result, but it is being given a place within a scale of worth.
Examples of binary variables
– A study related to the number of people who have died of pancreatic cancer at a given hospital during a specified time period. In this case, the variables 1 and 0 can be applied to the values »died from pancreatic cancer» and «died from conditions other than pancreatic cancer», respectively.
– Population censuses in which you want to determine how many men and how many women live in a certain geographical area. In this case, the value «1» can be related to men and the value «0» to women.
– A survey through which you want to know how many university students from a certain sector agree with the educational measures proposed by the government entity. The value «1» can be associated with the affirmative answer and the value «2» can be associated with the negative answer.
Examples of nominal variables
– A survey in a specific community that seeks to know the opinion of the neighbors in relation to the preferred colors to paint the facade of the building where they live. In this case the options can be white, beige, light blue or light green.
– A survey carried out in a certain municipality whose intention is to know the number of foreigners who live in said space considering a specific period. The nominal variables can be Colombian, Peruvian, Venezuelan or Ecuadorian nationalities.
– A sociological study that delves into the main communication channels through which the inhabitants of a specific sector obtain the news information they consume. The variables considered can be television newscasts, radio newscasts, Facebook or Twitter.
Examples of ordinal variables
– A study carried out by a clothing store that seeks to measure the level of customer satisfaction. The variables considered in this case can be «very satisfied», «moderately satisfied» and «dissatisfied».
– Surveys carried out by the government bodies of a specific country to determine the educational conditions of its inhabitants. The variables to take into account can be «low educational level», «medium educational level» and «high educational level».
– A survey carried out in a classroom after having given tools related to a specific topic, with the intention of verifying if the contents taught have been well understood by the students. According to the answers of the students, the following ordinal variables can be used: “very good”, “good”, “regular”, “bad” and “very bad”.
References
«Characteristics of binary variables» in Andalusian Society of Intensive Medicine and Coronary Units. Retrieved on October 22, 2019 in the Andalusian Society of Intensive Medicine and Coronary Units: samiuc.es
“Variable Measurement Level” in the IBM Knowledge Center. Retrieved on October 22, 2019 at the IBM Knowledge Center: ibm.com
«Binary variables – the cost of bauxite»in Industrial Engineering Online. Retrieved on October 22, 2019 in Industrial Engineering Online: ingenieríaindustrialonline.com
«Statistical variables» in the National Institute of Educational Technologies and Teacher Training. Retrieved on October 22, 2019 at the National Institute of Educational Technologies and Teacher Training: educalab.es
«Types of data» in National Institute of Educational Technologies and Teacher Training. Retrieved on October 22, 2019 at the National Institute of Educational Technologies and Teacher Training: educalab.es
«Statistical variable» in EcuRed. Retrieved on October 22, 2019 in EcuRed: ecured.cu
«Qualitative variable» in Economic Encyclopedia. Retrieved on October 22, 2019 in the Economic Encyclopedia: enciclopediaeconomica.com
“Qualitative variable” in MBA skool. Retrieved on October 22, 2019 at MBA skool: mbaskool.com
“Qualitative versus quantitative” at Southeastern Louisiana University. Retrieved on October 22, 2019 at Southeastern Louisiana University: southestaern.edu