Predicting the Unpredictable: Regression for Real-World Problems

Описание: 🚀 UNILORIN R Users Group Workshop Series: Predicting the Unpredictable: Regression for Real-World Problems

Join us for another insightful session in the Unilorin R User Group Meetup Series. This edition focuses on how to use R to explore relationships among variables and build predictive models that address real-world challenges. The session is designed to guide participants from foundational concepts to practical application, ensuring a smooth learning experience.

🔍 Audience Takeaways

Participants will gain hands-on understanding and practical skills for integrating AI tools into R. Key learning points include:

Correlation Analysis in R: Start with the basics by examining how two variables move together. You’ll learn how to compute and interpret correlation coefficients and understand when correlation can hint at predictive potential.

Introduction to Regression in R: Building on correlation, you’ll be introduced to regression as a more powerful tool for quantifying relationships and making predictions. This section explains what regression is, why it matters, and how it improves on simple correlation.

Core Regression Techniques: Deepen your understanding through hands-on exploration of simple linear regression, multiple regression, and essential model diagnostics. You’ll learn how to check assumptions, measure model performance, and interpret outputs accurately.

Data Analysis Workflow for Predictive Modelling: See how everything fits together as you walk through a full workflow: importing data, cleaning and preparing it, exploring patterns, building models, and evaluating results using tidyverse tools.

Real-World Use Case: Predicting Outcomes with R: Finally, apply what you've learned to a real dataset. This case study demonstrates how regression models can address real-world questions and support data-driven decision-making.

This session is designed to be practical, engaging, and accessible for participants at all levels. You’ll leave with a solid understanding of how to move from identifying relationships in data to building reliable predictive models using R.

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