Linear Regression is used when our response is qualitative and logistic regression is used when our response is qualitative. Logistic Regression applied a sigmoid function to our OLS model and bounds the output range to (0,1). In linear regression, we use the residual sum of squares as the minimization function whereas in Logistic we maximize the maximum likelihood function.