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The data include quantitative variables =, …, and qualitative variables =, …,.. is a quantitative variable. We note: . (,) the correlation coefficient between variables and ;; (,) the squared correlation ratio between variables and .; In the PCA of , we look for the function on (a function on assigns a value to each individual, it is the case for initial variables and principal components ...
Qualitative methods might be used to understand the meaning of the conclusions produced by quantitative methods. Using quantitative methods, it is possible to give precise and testable expression to qualitative ideas. This combination of quantitative and qualitative data gathering is often referred to as mixed-methods research. [14]
It plays an important theoretical role because it opens the way to the simultaneous treatment of quantitative and qualitative variables. Two methods simultaneously analyze these two types of variables: factor analysis of mixed data and, when the active variables are partitioned in several groups: multiple factor analysis.
Multiple factor analysis (MFA) is a factorial method [1] devoted to the study of tables in which a group of individuals is described by a set of variables (quantitative and / or qualitative) structured in groups.
A categorical variable that can take on exactly two values is termed a binary variable or a dichotomous variable; an important special case is the Bernoulli variable. Categorical variables with more than two possible values are called polytomous variables ; categorical variables are often assumed to be polytomous unless otherwise specified.
Qualitative research is a type of research that aims to gather and analyse non-numerical (descriptive) data in order to gain an understanding of individuals' social reality, including understanding their attitudes, beliefs, and motivation.
For example, qualitative data analysis often involves a fairly structured approach to coding raw data into systematic information and quantifying intercoder reliability. [2] There is often a more complex relationship between "qualitative" and "quantitative" approaches than would be suggested by drawing a simple distinction between them.
Quantitative analysis also takes a deductive approach. [8] Examples of content-analytical variables and constructs can be found, for example, in the open-access database DOCA. This database compiles, systematizes, and evaluates relevant content-analytical variables of communication and political science research areas and topics.