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This is a list of statistical procedures which can be used for the analysis of categorical data, also known as data on the nominal scale and as categorical variables.
Categorical data is the statistical data type consisting of categorical variables or of data that has been converted into that form, for example as grouped data. More specifically, categorical data may derive from observations made of qualitative data that are summarised as counts or cross tabulations , or from observations of quantitative data ...
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In statistics, multiple correspondence analysis (MCA) is a data analysis technique for nominal categorical data, used to detect and represent underlying structures in a data set. It does this by representing data as points in a low-dimensional Euclidean space .
Data analysis is the process of inspecting, cleansing, ... Data may be numerical or categorical (i.e., a text label for numbers). [13] Data collection.
Univariate analysis is the simplest form of analyzing data. Uni means "one", so the data has only one variable . [4] Univariate data requires to analyze each variable separately. Data is gathered for the purpose of answering a question, or more specifically, a research question.
When classification is performed by a computer, statistical methods are normally used to develop the algorithm.. Often, the individual observations are analyzed into a set of quantifiable properties, known variously as explanatory variables or features.