Statistical data types | Categorical data

Categorical variable

In statistics, a categorical variable (also called qualitative variable) is a variable that can take on one of a limited, and usually fixed, number of possible values, assigning each individual or other unit of observation to a particular group or nominal category on the basis of some qualitative property. In computer science and some branches of mathematics, categorical variables are referred to as enumerations or enumerated types. Commonly (though not in this article), each of the possible values of a categorical variable is referred to as a level. The probability distribution associated with a random categorical variable is called a categorical distribution. 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 grouped within given intervals. Often, purely categorical data are summarised in the form of a contingency table. However, particularly when considering data analysis, it is common to use the term "categorical data" to apply to data sets that, while containing some categorical variables, may also contain non-categorical variables. 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. Discretization is treating continuous data as if it were categorical. Dichotomization is treating continuous data or polytomous variables as if they were binary variables. Regression analysis often treats category membership with one or more quantitative dummy variables. (Wikipedia).

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From playlist R Tutorial | Rstudio

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From playlist WK1 Numbers and Variables - Online Statistics for the Flipped Classroom

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From playlist Forming Variables for Statistics & Statistical Software (WK 2 - QBA 237)

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From playlist Types of Variables

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From playlist Statistics

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This video is brought to you by the Quantitative Analysis Institute at Wellesley College. The material is best viewed as part of the online resources that organize the content and include questions for checking understanding: https://www.wellesley.edu/qai/onlineresources

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Related pages

Logistic regression | Word embedding | Mode (statistics) | Grouped data | Binary variable | Regression analysis | Contingency table | Level of measurement | Dummy variable (statistics) | Statistics | Continuous function | Qualitative property | Multinomial logistic regression | Nominal category | Dirichlet process | Discrete choice | Language model | Nonparametric statistics | List of analyses of categorical data | Interaction (statistics) | Nominal scale | Central tendency | Multinomial probit | Discretization | Statistical data type | Multinomial distribution | Probability distribution | Y-intercept | Orthogonality | Random variable | Equivalence relation | Grand mean | Categorical distribution | Bernoulli distribution