Introductory Business Statistics 2e aligns with the topics and objectives of the typical one-semester statistics course for business, economics, and related majors. The text provides detailed and supportive explanations and extensive step-by-step walkthroughs. The author places a significant emphasis on the development and practical application of formulas so that students have a deeper understanding of their interpretation and application of data. Problems and exercises are largely centered on business topics, though other applications are provided in order to increase relevance and showcase the critical role of statistics in a number of fields and real-world contexts. The second edition retains the organization of the original text. Based on extensive feedback from adopters and students, the revision focused on improving currency and relevance, particularly in examples and problems. This is an adaptation of Introductory Business Statistics 2e by OpenStax. You can access the textbook as pdf for free at openstax.org. Minor editorial changes were made to ensure a better ebook reading experience. Textbook content produced by OpenStax is licensed under a Creative Commons Attribution 4.0 International License.

A clear and concise introduction to statistics for business and management students, demonstrating how important statistics are in the business decision-making process and covering everything from conducting a survey and collecting data, to summarizing statistical data, and presenting findings. Each chapter features a real-world business situation and accompanying dataset, the reader is then encouraged to identify the correct statistical concept in the chapter and solve the problem outlined. Offering students a chance to use the newly learned theory in a practical way. New to the second edition: A "Review of Essential Mathematics" prologue, featuring tests and further links to help students refresh their knowledge of the core mathematical concepts used to calculate basic statistics. Updated screenshots on using IBM SPSS and Excel. A "Statistics in the Real World" feature included at the end of each chapter, demonstrating how statistics are applied in real-world business settings and research, accompanied by reflective questions. Updated case studies, examples and diagrams, illustrating key points and helping to reinforce learning. The book is accompanied by free online resources including step-by-step video tutorials on how to use Excel and IBM SPSS, datasets and worked solutions, an Instructors’ Manual, Testbank, and PowerPoint presentation slides for lecturers. Essential reading for business students wanting to know how to use statistics in a business setting.

A clear and concise introduction to statistics for business and management students, demonstrating how important statistics are in the business decision-making process and covering everything from conducting a survey and collecting data, to summarizing statistical data, and presenting findings. Each chapter features a real-world business situation and accompanying dataset, the reader is then encouraged to identify the correct statistical concept in the chapter and solve the problem outlined. Offering students a chance to use the newly learned theory in a practical way. New to the second edition: A “Review of Essential Mathematics” prologue, featuring tests and further links to help students refresh their knowledge of the core mathematical concepts used to calculate basic statistics. Updated screenshots on using IBM SPSS and Excel. A “Statistics in the Real World” feature included at the end of each chapter, demonstrating how statistics are applied in real-world business settings and research, accompanied by reflective questions. Updated case studies, examples and diagrams, illustrating key points and helping to reinforce learning. The book is accompanied by free online resources including step-by-step video tutorials on how to use Excel and IBM SPSS, datasets and worked solutions, an Instructors’ Manual, Testbank, and PowerPoint presentation slides for lecturers. Essential reading for business students wanting to know how to use statistics in a business setting.

Highly praised for its clarity and great examples, Weiers' INTRODUCTION TO BUSINESS STATISTICS, 6E introduces fundamental statistical concepts in a conversational language that connects with today's students. Even those intimidated by statistics quickly discover success with the book's proven learning aids, outstanding illustrations, non-technical terminology, and hundreds of current examples drawn from real-life experiences familiar to students. A continuing case and contemporary applications combine with more than 100 new or revised exercises and problems that reflect the latest changes in business today with an accuracy you can trust. You can easily introduce today's leading statistical software and teach not only how to complete calculations by hand and using Excel, but also how to determine which method is best for a particular task. The book's student-oriented approach is supported with a wealth of resources, including the innovative new CengageNOW online course management and learning system that saves you time while helping students master the statistical skills most important for business success.

Introductory Statistics 2e provides an engaging, practical, and thorough overview of the core concepts and skills taught in most one-semester statistics courses. The text focuses on diverse applications from a variety of fields and societal contexts, including business, healthcare, sciences, sociology, political science, computing, and several others. The material supports students with conceptual narratives, detailed step-by-step examples, and a wealth of illustrations, as well as collaborative exercises, technology integration problems, and statistics labs. The text assumes some knowledge of intermediate algebra, and includes thousands of problems and exercises that offer instructors and students ample opportunity to explore and reinforce useful statistical skills. This is an adaptation of Introductory Statistics 2e by OpenStax. You can access the textbook as pdf for free at openstax.org. Minor editorial changes were made to ensure a better ebook reading experience. Textbook content produced by OpenStax is licensed under a Creative Commons Attribution 4.0 International License.

This is an introductory statistics textbook for business and management students which uses the innovative approach of 'statistical thinking'. Statistics courses are essential for business students but traditional teaching methods are often seen as difficult and are therefore unpopular; this book aims to offer a new and more appealing way of learning to this market. 'An Introduction to Statistical Analysis for Business and Industry' presents a new and innovative introduction to statistics which trains students directly to address problems which commonly arise in business and industry. Having read and worked through the book and its accompanying manual, students should have the essential skills necessary to apply statistical thinking in business and be able to: –recognise statistical variation in processes, –apply a statistical problem-solving strategy for process improvement, –select and apply appropriate methods of statistical analysis.

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.