The statement which is not true of logistic regression is: a. Outcomes need to be categorical nominal.
A logistic regression can be defined as a predictive analysis that can be used to model the probability of a categorical event or class existing.
Basically, a logistic regression is a classification model that can be used to predict a dependent data variable (binary outcome) by analyzing the relationship existing between one or more independent data variables.
Some of the characteristics of logistic regression include the following:
- There must be interaction terms in a logistic regression model.
- The strength of results in a logistic regression model can be expressed using odds ratios (OR).
- The underlying equation (math) can be used to model the probability of a specific outcome occurring.
- A logistic regression model must contain a categorical data such as: pass or fail, good or bad, tall or short, alive or dead, yes or no, win or lose, etc.
In conclusion, the outcome of a logistic regression model need not to be categorical but a nominal data (binary outcome).
Read more: https://brainly.com/question/21344316
