This course offers a comprehensive introduction to the principles and practices of statistics with a strong emphasis on their application in business and managerial contexts. Designed to build analytical and quantitative reasoning, the course covers foundational concepts such as descriptive statistics, probability, and sampling, before progressing to advanced tools like hypothesis testing, regression analysis, and decision theory. Students explore various types of data, probability distributions, and inferential techniques to analyze and interpret business data effectively. Topics such as the Central Limit Theorem, confidence intervals, and non-parametric tests are introduced to support sound decision-making under uncertainty. A significant focus is also given to real-world applications through correlation and regression modeling, time series analysis, and decision trees, equipping students to handle diverse business problems with statistical insight. By the end of the course, learners will be able to collect relevant data, apply suitable statistical methods, interpret outputs meaningfully, and make evidence-based business decisions in uncertain environments.