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Principles of Data Science

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Principles of Data Science

Dr. Shaun V. Ault; Dr. Soohyun Nam Liao; Larry Musolino; Wisam Bukaita · OpenStax, Rice University

Principles of Data Science is intended to support one- or two-semester courses in data science. It is appropriate for data science majors and minors as well as students concentrating in business, finance, health care, engineering, the sciences, and a number of other fields where data science has become critically important. The authors have included a diverse mix of scenarios, examples, and data types for analysis and discussion purposes. These include both fictional contexts and real-world sources, such as the Federal Reserve Economic Database and Nasdaq. Data sets focus on a range of topics: business, science, social sciences. Applications include healthcare, physical sciences, demographics, policy, and finance. Data ethics and the emergence of artificial intelligence are covered deeply – both in their own chapters and as consistent threads throughout the course material. The authors and contributors have developed rich in-chapter example problems and extensive practice exercises that encourage students to apply concepts in a variety of situations. Technical illustrations and Python code support and supplement the principles and theory. The text also includes direct links to downloadable data sets and Python code, as well as guidance on how to use them.

CC BY-NC-SAComputer ScienceBusiness 0 lượt xem
Introductory Business Statistics 2e

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Introductory Business Statistics 2e

Alexander Holmes; Barbara Illowsky; Susan Dean; Nancy Foreman · OpenStax, Rice University

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. A detailed transition guide is available for instructors. The first edition of Introductory Business Statistics by OpenStax is available in web view here.

CC BY-NC-SABusinessMath 0 lượt xem