Which method is specifically designed for binary outcome predictions?

Which method is specifically designed for binary outcome predictions?

• A. Multiple Linear Regression
• B. Logistic Regression
• C. Linear Regression
• D. Scatter Plot

Answer: (B)

Logistic regression is specifically designed for binary outcome predictions because it uses the logistic function to model the probability that a given input point belongs to a particular category. In the context of binary outcomes, the target variable is categorical, taking on only two possible values, often represented as 0 and 1. Logistic regression transforms the linear combination of input features using the logistic function, which constrains the output to fall within the range of 0 and 1, making it interpretable as a probability. In contrast, multiple linear regression and linear regression are designed for predicting continuous outcome variables rather than binary outcomes. These methods produce outputs that can take any real value, which is not appropriate for situations where the outcome is confined to two discrete categories. A scatter plot is a graphical representation of data points and is not a prediction method; it visually displays the relationship between two continuous variables rather than predicting binary outcomes. Thus, logistic regression is the correct choice for problems involving binary classification.

Logistic regression is specifically designed for binary outcome predictions because it uses the logistic function to model the probability that a given input point belongs to a particular category. In the context of binary outcomes, the target variable is categorical, taking on only two possible values, often represented as 0 and 1. Logistic regression transforms the linear combination of input features using the logistic function, which constrains the output to fall within the range of 0 and 1, making it interpretable as a probability.

In contrast, multiple linear regression and linear regression are designed for predicting continuous outcome variables rather than binary outcomes. These methods produce outputs that can take any real value, which is not appropriate for situations where the outcome is confined to two discrete categories. A scatter plot is a graphical representation of data points and is not a prediction method; it visually displays the relationship between two continuous variables rather than predicting binary outcomes. Thus, logistic regression is the correct choice for problems involving binary classification.