Understanding Logistic Regression

What is the primary characteristic of a binary logistic regression?

• It requires only one independent variable.

• It is used when the outcome variable has two possible values.

• It predicts outcomes with more than two categories.

• It uses a continuous dependent variable.

In the given example, what are the independent variables used to predict the likelihood of a disease?

• Medication and age

• Age and gender

• Medication and gender

• Diet and exercise

How does a linear regression differ from a logistic regression in terms of the dependent variable?

• Linear regression uses a binary dependent variable.

• Logistic regression uses a categorical dependent variable with more than two categories.

• Logistic regression uses a continuous dependent variable.

• Linear regression uses a metric dependent variable.

What does a logistic regression model estimate in the context of disease prediction?

• The exact age of a person

• The probability of a person being diseased

• The exact time a person will get a disease

• The number of medications a person should take

In logistic regression, what do the values '1' and '0' typically represent?

• 1 for not diseased, 0 for diseased

• 1 for failure, 0 for success

• 1 for diseased, 0 for not diseased

• 1 for success, 0 for failure