Defining the sample size is an important step in quantitative research.
Quantitative research is a mode of research development that is based on the quantification of data . It is a strategy that seeks to obtain empirical evidence of the phenomena it observes based on measurements and statistical analysis.
The expression of the results of quantitative research, therefore, is done through numbers . The generalization of these results through deductive reasoning makes it possible to produce a hypothesis about what was studied.
Characteristics of quantitative research
Quantitative research is based on the analysis of statistics . From sampling , which occurs with the selection of a set of elements that represent a larger population , variables are examined to find patterns, calculate averages and discover frequencies.
In this way, it is possible to study the causality and effects of phenomena and generalize observations to propose hypotheses or demonstrate theories. Numerical magnitudes and graphs support the dissemination of the conclusions.
It is usually indicated that quantitative research offers, in the first instance, results that are descriptive . Statistics allow us to generalize these numbers and transfer what was appreciated in the sample to a broader population.
It can be stated that quantitative research constitutes an analysis tool. It must be replicable (that is, other researchers must be able to repeat its steps) and, therefore, allow for a direct comparison of its results.
In quantitative research, the intervening variables can have different characteristics.
Sampling types
A quantitative investigation can use different types of sampling . It must be clarified that, before obtaining the sample, it is essential to specify the definition of the population.
It is understood that the population is all those elements that have the characteristics, qualities or properties that are intended to be analyzed in the research . The sample , in this framework, is a subset of the population.
Sampling can be carried out in different ways. Random sampling is one in which, when determining the sample , all the elements that are part of the population have a probability of being selected.
Stratified sampling , on the other hand, requires the separation of a specific stratum or segment of the population. Other types are systematic sampling (elements from a first random selection are chosen at intervals), quota sampling (elements are chosen for their characteristics) and cluster sampling (random selection of groups of heterogeneous elements but with characteristics in common).
Artificial intelligence can contribute to the development of quantitative research.
Bias in quantitative research
Bias in quantitative research is a problem since it undermines the validity of the results. Selection bias , for example, implies an error when choosing the elements of the sample, then distorting the statistical analysis.
Measurement bias , also called information bias or observation bias , is an effect of experimental error that leads to misclassification . Confounding bias , for its part, arises due to the intervention of a factor that alters the association between other variables.
What these biases do is lead to the comparison of elements that are not comparable. The cause of this defect, ultimately, can be found in the way the sample is established, in the way the data is obtained or in the manipulation of variables.
Differences with the qualitative method
Quantitative research presents several differences with the qualitative method . In qualitative research there are no statistical analyses, mathematical studies or numerical operations: what the researcher does is collect descriptive data to interpret them inductively.
In this strategy, the hypotheses are not raised a priori. Questions arise as the investigation progresses, as do the answers that are proposed as possible.
While quantitative research appeals to experimentation and uses formal languages and magnitudes, qualitative research states its results with verbal discourse.
It is often indicated that quantitative research is object-centered, unlike qualitative research that focuses on the subject. For this reason, quantitative research is associated with objectivity and qualitative research is associated with subjectivity .
Stages of quantitative research
There are five stages of quantitative research , at least if the main phases are considered. The first stage is called conceptual and consists of the circumscription of the problem, the development of the theoretical framework and the elaboration of the hypothesis.
Then comes the design stage, linked to the layout of strategies and the choice of techniques. Quantitative research continues with the empirical stage (data collection), the analytical stage (analysis and interpretation) and finally the dissemination stage (communication of the conclusions).
These phases, sometimes, do not develop with such clear differentiation. The delimitation of the problem and research planning can be carried out together or simultaneously, to mention one possibility.