Probability and Statistics for Data-Driven Decisions

Every critical business decision involves some degree of uncertainty. Understanding how to quantify this uncertainty and interpret data relationships is the key to making smart, evidence-based choices. This course equips you with the essential tools of probability and statistics, transforming how you analyze risk and evaluate options. Through clear, written explanations and practical scenarios, you will learn to transition from intuitive guessing to structured, data-driven reasoning. What you'll learn: • Understand foundational probability concepts, including conditional probability and Bayes' theorem. • Analyze data distributions and central tendencies to summarize complex datasets. • Interpret statistical significance and hypothesis testing to validate business assumptions. • Evaluate data relationships using correlation and basic regression models. • Apply statistical principles to modern decision-making frameworks like A/B testing. • Quantify uncertainty and risk to support strategic planning and forecasting. The course begins with core terminology and foundational definitions before guiding you through data analysis, hypothesis testing, and practical decision-making models. You will progress step-by-step through written explanations and realistic scenarios designed to build your analytical confidence. This course is designed for absolute beginners, including aspiring data analysts, business managers, and decision-makers, with no prior advanced mathematics or statistical background required. Start building your analytical foundation and make more confident decisions today.