The correct answer is: B. linear, binary
Logistic regression is a statistical method that uses a logistic function to model the probability of a binary outcome. The logistic function is a non-linear function that maps a real number to a number between 0 and 1. This makes it well-suited for modeling binary outcomes, which can only take on two values, such as “success” or “failure”.
Logistic regression is a powerful tool that can be used to model a wide variety of data. It is often used in the fields of medicine, marketing, and economics.
Here is a brief explanation of each option:
- A. linear, numeric
Linear regression is a statistical method that uses a linear function to model the relationship between two variables. The linear function is a straight line that maps two real numbers to another real number. This makes it well-suited for modeling numeric data, which can take on any real number value.
However, linear regression cannot be used to model binary outcomes, because the logistic function is not a linear function.
- B. linear, binary
This is the correct answer. Logistic regression is a linear regression technique that is used to model data having a binary outcome.
- C. nonlinear, numeric
Nonlinear regression is a statistical method that uses a non-linear function to model the relationship between two variables. The non-linear function is a curve that maps two real numbers to another real number. This makes it well-suited for modeling numeric data, which can take on any real number value.
However, nonlinear regression cannot be used to model binary outcomes, because the logistic function is not a non-linear function.
- D. nonlinear, binary
This is not the correct answer. Logistic regression is a linear regression technique that is used to model data having a binary outcome.