Introduction to the basics of applied statistics for decision-making and for assessing risk and uncertainty. The course will mainly cover the broadly defined subjects of descriptive statistics, probability, decision trees, random variables, random sampling, hypothesis testing for continuous/categorical data and regression analysis/model building. Course delivery will be a mix of lectures, hands-on problem solving and data-driven case discussions led by students.