Digital library
Textbooks, references and open learning resources.
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Principles of Finance 2e
Julie Dahlquist; Rainford Knight; Alan S. Adams; Curtis J. Bacon · OpenStax, Rice University
Designed to meet the scope and sequence of your course, Principles of Finance 2e provides a strong foundation in financial applications using an innovative use-case approach to explore their role in business decision-making. An array of financial calculator and downloadable Microsoft Excel data exercises also engage students in experiential learning throughout. With flexible integration of technical instruction and data, this title prepares students for current practice and continual evolution. The first edition of Principles of Finance by OpenStax is available in web view here.
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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.