Data Analysis and Predictive Modeling with R

R is one of the most powerful languages for statistical computing, but starting your data journey can feel overwhelming without a structured path. This text-based course guides you step-by-step through the foundational concepts of data analysis, statistical tests, and predictive modeling. You will transition from understanding basic R syntax to confidently preparing data, running statistical evaluations, and constructing predictive models. Through clear written explanations and practical code-focused exercises, you will develop the skills to extract meaningful insights from raw datasets. What you'll learn: - Understand foundational R syntax, data types, and core statistical terminology - Clean and manipulate datasets efficiently using modern tidyverse packages - Apply essential statistical tests to discover patterns and relationships in data - Build and evaluate linear and logistic regression models for predictive analysis - Implement modern best practices for reproducible data workflows and reporting The course begins with key definitions and fundamental concepts before progressing to hands-on data manipulation. You will then explore statistical hypothesis testing and finish by constructing robust predictive models using real-world scenarios. This course is designed for beginners who want to learn data analysis and predictive modeling from scratch, with no prior programming experience or advanced statistical background required. Start reading today to unlock the power of R for data-driven decision-making.