True or False: Linear regression models can be used to predict a binary dependent variable.

True or False: Linear regression models can be used to predict a binary dependent variable.

• A. True
• B. False
• C. Only under specific conditions
• D. Only for categorical variables

Answer: (B)

Linear regression models are primarily designed for predicting continuous dependent variables, not binary ones. In the context of a binary dependent variable (which takes on two possible outcomes, such as yes/no or 0/1), using standard linear regression can lead to several issues. For example, the predictions made by a linear regression model can fall outside the range of 0 and 1, which is not interpretable for binary outcomes. Additionally, the assumptions of linear regression, such as homoscedasticity and normality, do not hold when the dependent variable is binary. Instead, logistic regression is commonly used for binary dependent variables because it models the probability that a certain event occurs. The logistic function ensures that the predicted probabilities remain within the range of 0 and 1, providing meaningful interpretations of the outcomes. The assertion that linear regression could be used for binary outcomes is misleading, which validates the response indicating that this statement is false.

Linear regression models are primarily designed for predicting continuous dependent variables, not binary ones. In the context of a binary dependent variable (which takes on two possible outcomes, such as yes/no or 0/1), using standard linear regression can lead to several issues.

For example, the predictions made by a linear regression model can fall outside the range of 0 and 1, which is not interpretable for binary outcomes. Additionally, the assumptions of linear regression, such as homoscedasticity and normality, do not hold when the dependent variable is binary.

Instead, logistic regression is commonly used for binary dependent variables because it models the probability that a certain event occurs. The logistic function ensures that the predicted probabilities remain within the range of 0 and 1, providing meaningful interpretations of the outcomes.

The assertion that linear regression could be used for binary outcomes is misleading, which validates the response indicating that this statement is false.