Linear regression is used in a variety of sectors, including economics (predicting sales based on advertising spend), finance (predicting stock prices), and healthcare (predicting patient recovery time using a variety of criteria). Logistic regression, on the other hand, is commonly used in classification tasks such as spam email detection, medical diagnosis (predicting illness presence), and credit risk assessment (predicting if a customer will fail on a loan). Both strategies are vital to predictive modelling and play critical roles in analysing variable interactions and generating data-driven judgements.
