Business Analytics: Methods and Cases for Data-Driven Decisions [Hardcover]

A comprehensive, innovative textbook suitable for senior and graduate students in business or data science departments.Business analytics is about leveraging data analysis and analytical modeling methods to achieve business objectives. Suitable for senior and graduate students in business or data science, this innovative text presents methods in an intuitive fashion and backs up business applications with an approachable level of mathematical rigor.Business analytics is about leveraging data analysis and analytical modeling methods to achieve business objectives. Suitable for senior and graduate students in business or data science, this innovative text presents methods in an intuitive fashion and backs up business applications with an approachable level of mathematical rigor.Business analytics is all about leveraging data analysis and analytical modeling methods to achieve business objectives. This is the book for upper division and graduate business students with interest in data science, for data science students with interest in business, and for everyone with interest in both. A comprehensive collection of over 50 methods and cases is presented in an intuitive style, generously illustrated, and backed up by an approachable level of mathematical rigor appropriate to a range of proficiency levels. A robust set of online resources, including software tools, coding examples, datasets, primers, exercise banks, and more for both students and instructors, makes the book the ideal learning resource for aspiring data-savvy business practitioners.Executive Overview; 1. Data and Decisions; 1.1 Learning Objectives; 1.2 Introduction; 1.3 Data-to-Decision Process Model; 1.4 Decision Models; 1.5 Sensitivity Analysis; 2. Data Preparation; 2.1 Learning Objectives; 2.2 Data Objects; 2.3 Selection; 2.4 Amalgamation; 2.5 Synthetic Variables; 2.6 Normalization; 2.7 Dummy Variables; 2.8 CASE | High-Tech Stocks; 3. Data Exploration; 3.1 Learning Objectives; 3.2 Descriptive Statisticsl³ø