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In statistics, multinomial logistic regression is a classification method that generalizes logistic regression to multiclass problems.

Multinomial logistic regression is used when the dependent variable in question is nominal (equivalently categorical, meaning that it falls into any one of a set of categories that cannot be ordered in any meaningful way) and for which there are more than two categories.

The Paired-Samples T Test procedure compares the means of two variables for a single group. The procedure computes the differences between values of the two variables for each case and tests whether the average differs from 0.

Binary Logistic Regression is defined as a type of regression analysis used when the dependent variable is binary, meaning it has two categories.

Logistic Regression is a Machine Learning classification algorithm that is used to predict the probability of a categorical dependent variable.

Correlation analysis in research is a statistical method used to measure the strength of the linear relationship between two variables and compute their association.

An F-test is used to test if the variances of two populations are equal.

Regression analysis is a set of statistical methods used for the estimation of relationships between a dependent variable and one or more independent variables.

Multiple linear regression is a statistical technique that uses several explanatory variables to predict the outcome of a response variable.

Chi-square is used to measure the association between Variables.

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