Principles of Managerial Statistics and Data Science by Roberto Rivera (Author) delves into the fundamental principles of managerial statistics and data science, emphasizing statistical literacy for business students. Through a comprehensive exploration of both theoretical concepts and practical applications, this book introduces readers to key topics such as Big Data, data analytics, and data wrangling. Each chapter is enriched with numerous examples that illustrate how to apply these theories in real-world scenarios. The inclusion of over 100 open data sets from diverse regions around the world offers instructors flexibility and relevance by allowing them to tailor content to local contexts. Applications range from assessing racial biases in police searches in San Diego, to analyzing moisture and fat percentages in Canadian cheese, and modeling taxi fares in Chicago based on extensive ride data. Additionally, the book covers essential statistical topics including data visualization, descriptive measures, probability, confidence intervals, hypothesis testing, analysis of variance, simple and multiple linear regression, contingency tables, Chi-square tests, non-parametric methods, and time series methods. This textbook is designed to equip students with the necessary skills to navigate the complex landscape of managerial statistics and data science.