This project aims to analyze the factors influencing the success of marketing strategies using the Logistic Regression method. The dataset includes variables such as Advertising Budget, Salespeople, Customer Satisfaction, and Competition Level, with the target variable Success (1 = success, 0 = failure). Through this analysis, a predictive model is developed to estimate the probability of marketing success and evaluate its performance using statistical metrics such as accuracy and AUC.

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Técnica de validación y simulación