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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.
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