Regression analysis is arguably the single most powerful and widely applicable tool in any effective examination of common business issues. Every day, decision-makers face problems that require constructive actions with significant consequences, and regression procedures can prove a meaningful and valuable asset in the decision-making process. This text is designed to help students achieve a full understanding of regression and the many ways it can be used. Taking into consideration current statistical technology, Introductory Regression Analysis focuses on the use and interpretation of software, while also demonstrating the logic, reasoning, and calculations that lie behind any statistical analysis. Furthermore, the text emphasizes the application of regression tools to real-life business concerns. This multilayered, yet pragmatic approach fully equips students to derive the benefit and meaning of a regression analysis. This text is designed to serve in a second undergraduate course in statistics, focusing on regression and its component features. The material presented in this text will build from a foundation of the principles of data analysis. Although previous exposure to statistical concepts would prove helpful, all the material needed for an examination of regression analysis is presented here in a clear and complete form.

Regression analysis is arguably the single most powerful and widely applicable tool in any effective examination of common business issues. Every day, decision-makers face problems that require constructive actions with significant consequences, and regression procedures can prove a meaningful and valuable asset in the decision-making process. This text is designed to help students achieve a full understanding of regression and the many ways it can be used. Taking into consideration current statistical technology, Introductory Regression Analysis focuses on the use and interpretation of software, while also demonstrating the logic, reasoning, and calculations that lie behind any statistical analysis. Furthermore, the text emphasizes the application of regression tools to real-life business concerns. This multilayered, yet pragmatic approach fully equips students to derive the benefit and meaning of a regression analysis. This text is designed to serve in a second undergraduate course in statistics, focusing on regression and its component features. The material presented in this text will build from a foundation of the principles of data analysis. Although previous exposure to statistical concepts would prove helpful, all the material needed for an examination of regression analysis is presented here in a clear and complete form.

Applied Statistics: Examining Global Economic and Social Problems introduces students to the complex and relevant social, economic, and political problems that we face today through the use and application of foundational concepts in statistics. The text uses live data to show students the nature of and solutions to global issues such as income inequality, consumer and student debt, government deficits, corporate crime, and many other common dilemmas, illustrating the applied nature of statistics in a meaningful and concrete way. Over the course of 13 chapters, the book addresses topics including statistical analysis, graphs, computer applications, numerical measures, probability, and probability distribution. Students learn about sampling means and techniques, confidence intervals, hypothesis tests, the meaning of two populations, and simple regression and correlation analysis. Each chapter contains problems and exercises to help students better understand the role of statistics within the context of global challenges. Applied Statistics is well-suited for undergraduate and graduate business statistic courses, as well as social science courses with emphasis in statistical data.