Which regression technique is suitable for predicting binary outcomes? Linear regression Logistic regression Polynomial regression None of above

Logistic regression is the suitable technique for predicting binary outcomes. This is because logistic regression is used when the dependent variable is categorical in nature. In this case, the dependent variable is binary, meaning it has two possible outcomes. Linear and Polynomial regressions, on the other hand, are used when the dependent variable is continuous. Therefore, they are not suitable for predicting binary outcomes.

Logistic regression is the suitable technique for predicting binary outcomes. This is because logistic regression is used when the dependent variable is binary or dichotomous, meaning it only contains data coded as 1 (YES, success, etc.) or 0 (NO, failure, etc.). Unlike linear or polynomial regression, which are used to predict continuous outcomes, logistic regression allows you to model a relationship between multiple independent variables and a binary dependent variable.