Regression Analysis and Statistical Testing for Data Analytics

Every day, organizations collect vast amounts of data, but the real value lies in understanding how variables influence one another. Regression analysis is the foundational statistical tool that allows you to uncover these hidden relationships and predict future outcomes. In this text-only course, you will transition from a beginner to a confident analyst capable of setting up regression models and verifying their accuracy. You will learn how to interpret statistical outputs, validate your assumptions, and use diagnostic tools to ensure your models are robust and reliable. What you'll learn: - Understand the core principles of linear and logistic regression models - Evaluate model performance using confusion matrices and ROC curves - Apply key statistical tests to validate your data assumptions - Analyze relationships between multiple variables using modern data tools - Interpret regression coefficients and statistical significance with confidence You will start with the fundamental terminology of statistical modeling before moving step-by-step through simple linear regression, multiple regression, and classification metrics. Each concept is reinforced with clear written explanations and practical scenarios that you can read and apply immediately. This course is designed for aspiring data analysts, business professionals, and beginners who want to build a strong foundation in predictive modeling. No prior experience with advanced statistics or programming is required. Start reading today to unlock the predictive power of your data.