Quantitative investigation


Quantitative research is one that uses quantitative methods and statistical inference in order to extrapolate the results from a sample to a population.

Quantitative research, unlike qualitative, analyzes a high volume of data. In addition, it studies quantitative variables, that is, numerical. These acquire all their meaning when they are related to others through correlations, regressions or hypothesis tests.

Importance of quantitative research

Quantitative research is the only one that can draw conclusions that can be extrapolated to a larger group than the one investigated. Hence, its importance is, above all, because it allows generalization. In fact, hypothesis testing or regression aims to obtain results from a sample that serves the population.

But that does not mean that the qualitative occupies a lower hierarchical situation. In fact, this is usually the first step before quantitative, through exploratory investigations.

However, when we want to conduct a study that is conclusive, we must use numerical data. In addition, you have to work with large samples, because only then can they be inferred.

Characteristics of quantitative research

The characteristics of quantitative research are as follows:

  • The data used by this type of research is numerical and therefore measurable.
  • Generally, the process of obtaining the data is quick.
  • The conclusions obtained are accurate and supported by data and statistics.
  • Reduce the likelihood that research results are biased.
  • It allows predicting certain behaviors of the studied population.
  • The results obtained facilitate the understanding of the situation of the population.

Types of quantitative research

There are four different types when conducting quantitative research:

  • Experimental: In this type of research what is carried out is, as its name indicates, an experiment. In this way, with the chosen sample, the aim is to prove what happens by making changes to the environment.
  • Quasi-experimental: It has a certain relationship with the previous type but in this case it is not possible to isolate a part of the population (sample) to experiment only with these subjects.
  • Correlational: With quantitative correlation research, the aim is to identify certain correlations between the variables studied. For example, every time in a city the humidity reaches 80%, there is precipitation with a maximum of 0.5 liters per square meter.
  • Causal-comparative: Finally, this type of research tries to identify what cause-effect relationship occurs between two or more variables.

Steps to conduct a quantitative investigation

The steps to carry out a quantitative investigation are very similar to those carried out in others such as descriptive. However, they differ from the latter in that they go a step further and are not satisfied with just describing.

That said, let's see the steps to follow:

  • Define the problem: First, you have to define the problem. What do we want to know, the reasons why we need this information or what are the previous studies on the subject.
  • Methodology: Second, you have to choose the methodology. Based on the above, we must choose the techniques to use. Thus, we can perform a regression, if we want to know the movement of one variable with respect to others, or a hypothesis test, if we are going to extrapolate the results through statistical inference.
  • Analysis: Third, you have to carry out the analysis. In this case, statistical software, such as SPSS or similar, will be of great help. You have to perform the calculations and obtain the indicators of goodness of fit, confidence intervals, significance or any other necessary.
  • Interpretation of results: Finally, you have to interpret those results. The goodness of fit, being the R squared the best known, informs us of the predictive power of the regression. Confidence intervals and the significance of the validity of the hypothesis test

Quantitative Research Example

Imagine an investigation on the economic growth (GDP) of a country and the level of unemployment. We want to know if there is a relationship between both variables. Furthermore, previous studies show a possible inverse correlation between both variables. Therefore, we run a regression to confirm it.

In the image below, we show the process to follow:

Considering this image, we must emphasize that quantitative research usually has four steps:

  1. First, we wonder if there is a relationship between the variables GDP and unemployment.
  2. Then we propose the methodology, taking into account other works.
  3. Then the regression calculations are performed with its indicators.
  4. Finally, it is interpreted and, in this example, we conclude that it exists, but that it is not intense.

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