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Authors: Diez, Barr, Çetinkaya-Rundel, and Dorazio
Publisher: OpenIntro
License: CC BY-SA
We hope readers will take away three ideas from this book in addition to forming a foundationof statistical thinking and methods.
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Authors: Çetinkaya-Rundel and Hardin
Publisher: OpenIntro
License: CC BY-SA
Introduction to Modern Statistics is a re-imagining of a previous title, Introduction to Statistics with Randomization and Simulation. The new book puts a heavy emphasis on exploratory data analysis (specifically exploring multivariate relationships using visualization, summarization, and descriptive models) and provides a thorough discussion of simulation-based inference using randomization and bootstrapping, followed by a presentation of the related Central Limit Theorem based approaches. The second edition of IMS has updated datasets, additional exercises, a new application for chapter 3, and updated text and code to reflect changes in best practices.
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Authors: Illowsky, Dean, Birmajer, Blount, Boyd, Einsohn, Helmreich, Kenyon, Lee, and Taub
Publisher: OpenStax
License: CC BY
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.
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Authors: Shafer and Zhang
Publisher: Saylor Foundation
License: CC BY-NC-SA
In many introductory level courses today, teachers are challenged with the task of fitting in all of the core concepts of the course in a limited period of time. The Introductory Statistics teacher is no stranger to this challenge. To add to the difficulty, many textbooks contain an overabundance of material, which not only results in the need for further streamlining, but also in intimidated students. Shafer and Zhang wrote Introductory Statistics by using their vast teaching experience to present a complete look at introductory statistics topics while keeping in mind a realistic expectation with respect to course duration and students' maturity level.
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Authors: Mahbobi and Tiemann
Publisher: BCcampus
License: CC BY
Introductory Business Statistics with Interactive Spreadsheets – 1st Canadian Edition is an adaptation of Thomas K. Tiemann's book, Introductory Business Statistics. This new edition still contains the basic ideas behind statistics, such as populations, samples, the difference between data and information, and sampling distributions as well as information on descriptive statistics and frequency distributions, normal and t-distributions, hypothesis testing, t-tests, f-tests, analysis of variance, non-parametric tests, and regression basics. New topics include the chi-square test and categorical variables, null and alternative hypotheses for the test of independence, simple linear regression model, least squares method, coefficient of determination, confidence interval for the average of the dependent variable, and prediction interval for a specific value of the dependent variable.
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Authors: Holmes, Illowsky, and Dean
Publisher: OpenStax
License: CC BY
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.
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Author: Tiemann
Publisher: BCcampus
License: CC BY
The book "Introductory Business Statistics" by Thomas K. Tiemann explores the basic ideas behind statistics, such as populations, samples, the difference between data and information, and most importantly sampling distributions. The author covers topics including descriptive statistics and frequency distributions, normal and t-distributions, hypothesis testing, t-tests, f-tests, analysis of variance, non-parametric tests, and regression basics. Using real-world examples throughout the text, the author hopes to help students understand how statistics works, not just how to "get the right number."
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Authors: Illowsky and Dean
Publisher: OpenStax CNX
License: CC BY
Collaborative Statistics was written by Barbara Illowsky and Susan Dean, faculty members at De Anza Collegein Cupertino, California. The textbook was developed over several years and has been used in regularand honors-level classroom settings and in distance learning classes. Courses using this textbook have beenarticulated by the University of California for transfer of credit. The textbook contains full materials forcourse offerings, including expository text, examples, labs, homework, and projects. A Teacher's Guide iscurrently available in print form and on the Connexions site at and supplemental course materials including additional problem sets and video lectures are available. The on-line text for each of these collections collections willmeet the Section 508 standards for accessibility.
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Author: Poritz
Publisher: Colorado State University Pueblo
License: CC BY-SA
This is a first draft of a free (as in speech, not as in beer, [Sta02]) (although it is free as in beer as well) textbook for a one-semester, undergraduate statistics course. It was used for Math 156 at Colorado State University–Pueblo in the spring semester of 2017.
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Author: Kindratt
Publisher: Mavs Open Press
License: CC BY
National data sets provide an avenue for students to practice data analytic skills while also answering meaningful research questions. This open education resource was developed to train future public health professionals how to conduct secondary data analysis of national health surveys using SAS statistical software. SAS software was selected because it is one of the most commonly used software programs used among public health departments and academia. The book includes details on how to analyze public-use data from five common national health surveys, including the National Health Interview Survey (NHIS), Medical Expenditure Panel Survey (MEPS), Health Information National Trends Survey (HINTS), Behavior Risk Factor Surveillance System (BRFSS) and National Health and Nutrition and Examination Survey (NHANES). All datasets and corresponding syntax files are available from the Open ICPSR Data Repository.