Statistical Analysis and Modeling with SAS

Businesses rely on data to make critical strategic decisions, but raw data is useless without the right statistical models. This text-based course introduces you to the fundamentals of statistical analysis and predictive modeling using SAS. You will progress from understanding core statistical concepts to writing SAS programs that analyze variance, evaluate relationships between variables, and build predictive regression models. By the end of this course, you will be able to prepare data, run statistical tests, and interpret model outputs to solve real-world business problems. What you'll learn: - Understand foundational statistical concepts, hypothesis testing, and data validation techniques. - Perform Analysis of Variance (ANOVA) to compare group means and identify significant differences. - Build and evaluate predictive models using linear and logistic regression in SAS. - Diagnose and validate model assumptions to ensure reliability and avoid bias in your business insights. - Write clean, efficient SAS code to manipulate, filter, and prepare datasets for analysis. The course begins with foundational statistical definitions and data preparation techniques, before moving into programming concepts. You will read detailed explanations, analyze code examples, and practice interpreting statistical outputs. This course is designed for aspiring business analysts, data professionals, and beginners who want to learn statistical modeling with SAS. No prior programming or advanced statistics experience is required. Start building your analytical toolkit and learn how to turn data into predictive business decisions today.