Introduction to Scatterplots and Data Visualization

Scatterplots are essential analytical tools for discovering patterns, trends, and outliers across numerical datasets. This written course provides a thorough grounding in bivariate data visualization, guiding you from fundamental charting principles to nuanced data interpretation. You will build a strong conceptual understanding of how paired variables interact, how to identify linear and non-linear associations, and how to avoid common pitfalls in data representation. What you'll learn: - Understand core data visualization terminology, coordinate systems, and scaling methods - Identify linear, non-linear, positive, and negative correlations in bivariate datasets - Detect outliers, clusters, and data skewness through structured examination - Apply multidimensional techniques by integrating color encoding and size variations - Evaluate confounding variables and distinguish correlation from causation - Practice interpreting real-world datasets across business, science, and analytics domains The course begins with foundational vocabulary and chart mechanics before moving systematically into correlation analysis, dimensional encoding, and best practices for clear reporting. This course is designed for beginners, data enthusiasts, and analysts looking to solidify their charting fundamentals with no prior statistics background required. Start reading today to turn raw numbers into clear, actionable visual insights.