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  2. Multiple correspondence analysis - Wikipedia

    en.wikipedia.org/wiki/Multiple_correspondence...

    The Burt table is the symmetric matrix of all two-way cross-tabulations between the categorical variables, and has an analogy to the covariance matrix of continuous variables. Analyzing the Burt table is a more natural generalization of simple correspondence analysis , and individuals or the means of groups of individuals can be added as ...

  3. List of analyses of categorical data - Wikipedia

    en.wikipedia.org/wiki/List_of_analyses_of...

    Toggle the table of contents. List of analyses of categorical data. 2 languages. ... data, also known as data on the nominal scale and as categorical variables.

  4. Categorical variable - Wikipedia

    en.wikipedia.org/wiki/Categorical_variable

    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 ...

  5. Log-linear analysis - Wikipedia

    en.wikipedia.org/wiki/Log-linear_analysis

    Violations to this assumption result in a large reduction in power. Suggested solutions to this violation are: delete a variable, combine levels of one variable (e.g., put males and females together), or collect more data. 3. The logarithm of the expected value of the response variable is a linear combination of the explanatory variables.

  6. Correspondence analysis - Wikipedia

    en.wikipedia.org/wiki/Correspondence_analysis

    Correspondence analysis is performed on the data table, conceived as matrix C of size m × n where m is the number of rows and n is the number of columns. In the following mathematical description of the method capital letters in italics refer to a matrix while letters in italics refer to vectors .

  7. Logistic regression - Wikipedia

    en.wikipedia.org/wiki/Logistic_regression

    The data points are indexed by the subscript k which runs from = to = =. The x variable is called the "explanatory variable", and the y variable is called the "categorical variable" consisting of two categories: "pass" or "fail" corresponding to the categorical values 1 and 0 respectively.

  8. Dummy variable (statistics) - Wikipedia

    en.wikipedia.org/wiki/Dummy_variable_(statistics)

    The variable could take on a value of 1 for males and 0 for females (or vice versa). In machine learning this is known as one-hot encoding. Dummy variables are commonly used in regression analysis to represent categorical variables that have more than two levels, such as education level or occupation.

  9. Categorical distribution - Wikipedia

    en.wikipedia.org/wiki/Categorical_distribution

    A categorical distribution is a discrete probability distribution whose sample space is the set of k individually identified items. It is the generalization of the Bernoulli distribution for a categorical random variable. In one formulation of the distribution, the sample space is taken to be a finite sequence of integers.