Difference between qualitative and quantitative


Have we ever heard: "Quality is not the same as quantity." In this statement we find the main difference between qualitative and quantitative, both being a reference to quality (qualitative) and quantity (quantitative), respectively.

In other words, when we talk about the «qualitative» concept, according to the Royal Spanish Academy (RAE), we are talking about a quality, or related to a quality. In a study, the qualitative analysis would be more related to a more subjective analysis, based on variables that, in a certain way, cannot be measured exactly. That is, numerically.

On the other hand, when we talk about the «quantitative» concept, also according to the RAE, we are talking about a quantity, or something that is related to a quantity. In a study, the analysis of variables that can be measured numerically.

So, in summary, we are talking about two opposite concepts. While one focuses on qualities and quality, another refers to quantity. For this reason, in a study, qualitative analysis will focus on the qualities presented by the object of study, while quantitative analysis will focus on measurable variables that can be expressed numerically.

Therefore, to understand it better, let's see the difference between qualitative and quantitative, as well as the main differences found between each of these analysis methods.

Difference between qualitative and quantitative

So, let's see their main differences:

Qualitative analysis

Qualitative analysis focuses on understanding the phenomena that occur. But, for its understanding, it uses narrative data, it focuses on the study of literature, as well as individual characteristics and experiences. In other words, it focuses on data that is not expressed numerically.

Among these data that it collects, the qualitative analysis focuses on surveys, customer evaluations, as well as another series of data collection methods that offer us a qualitative vision of the object of study.

Qualitative analysis, in addition to being used to complement the quantitative one, is used to obtain information on a given topic. Thanks to this analysis, we can extract many opinions and, if true, higher quality information.

Since it is an analysis based on information that is not expressed by numbers, we are talking about a subjective analysis. A subjective analysis that, in addition, does not usually use random sampling, since, given the difficulty, the sample is usually selected.

The measurement cannot be standardized, as there is no numerical data that allows it. Also, the method of collecting data is more flexible than the quantitative method.

To measure the data, analyze it and interpret it, we must know that these, unlike the other method, are more difficult to analyze. Likewise, given that they are many data that we cannot homogenize, they must be analyzed throughout the study and could lead to continuous modifications until the end. This, in addition, leads us to a situation in which the conclusions are not final until the entire process is finished.

Quantitative analysis

Quantitative analysis, like qualitative, focuses on understanding the phenomena that occur. But, for your understanding, it uses numerical data, which allows us to extract the information. In other words, it is based on more reliable measurements, as it uses an analysis method that allows us to identify and quantify the problem.

Therefore, we are talking about data that can be expressed numerically. That is, surveys, indicators, studies, observations, ratios, as well as another series of tools that allow us to say that we are talking about an objective study.

For the selection of the sample, and since it is data, it can be done randomly. That is, we should not have any preference, since the data can be homogenized in a simple way. This is something that also facilitates the measurement of the problem, since it can be quantified and it is done in a standardized way. At the same time, it also presents a more structured and inflexible data collection method.

Once we have finished the study, the conclusions tend to be more reliable, since they are data that is extracted from correctly applied metrics. While, also, it allows us to obtain conclusions more quickly, once the study is finished, due to the fact that the information, as we said, can be homogenized and interpreted more comfortably.

In summary, we are talking about two very different approaches, but if they complement each other, they allow us to carry out a fairly reliable study.

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