👉 Logistics regression is used to test models in predicting categorical outcomes with two or more than two categories.
👉 The independent variable can be continuous, categorical or mix.
👉 The dependent variable is categorical (nominal or ordinal) with two or more categories.

👉 Logistics regression is classified as Binary and multinomial logistics regression.

Binary logistics regression

The categorical dependent  variable is dichotomous (two categories) like yes/no; fail/success; absent/present.

Multinomial logistics regression

The dependent variable has more than two categories.


Assumptions of logistics regression

Some of the assumptions of logistics regression include the following.

❤ Sample size must be greater than the number of predictors.
❤ Check the multicollinearity diagnosis test using tolerance value.
❤No assumption about the distribution scores of predictors.


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