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Author: Barbara Illowsky Publisher: ISBN: Category : Mathematics Languages : en Pages : 2106
Book Description
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.
Author: Barbara Illowsky Publisher: ISBN: Category : Mathematics Languages : en Pages : 2106
Book Description
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.
Author: Alexander Holmes Publisher: ISBN: Category : Business & Economics Languages : en Pages : 1801
Book Description
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.
Author: Peter Dalgaard Publisher: Springer Science & Business Media ISBN: 0387790543 Category : Mathematics Languages : en Pages : 370
Book Description
This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics. The main mode of presentation is via code examples with liberal commenting of the code and the output, from the computational as well as the statistical viewpoint. Brief sections introduce the statistical methods before they are used. A supplementary R package can be downloaded and contains the data sets. All examples are directly runnable and all graphics in the text are generated from the examples. The statistical methodology covered includes statistical standard distributions, one- and two-sample tests with continuous data, regression analysis, one-and two-way analysis of variance, regression analysis, analysis of tabular data, and sample size calculations. In addition, the last four chapters contain introductions to multiple linear regression analysis, linear models in general, logistic regression, and survival analysis.
Author: John Verzani Publisher: CRC Press ISBN: 1315360306 Category : Computers Languages : en Pages : 522
Book Description
The second edition of a bestselling textbook, Using R for Introductory Statistics guides students through the basics of R, helping them overcome the sometimes steep learning curve. The author does this by breaking the material down into small, task-oriented steps. The second edition maintains the features that made the first edition so popular, while updating data, examples, and changes to R in line with the current version. See What’s New in the Second Edition: Increased emphasis on more idiomatic R provides a grounding in the functionality of base R. Discussions of the use of RStudio helps new R users avoid as many pitfalls as possible. Use of knitr package makes code easier to read and therefore easier to reason about. Additional information on computer-intensive approaches motivates the traditional approach. Updated examples and data make the information current and topical. The book has an accompanying package, UsingR, available from CRAN, R’s repository of user-contributed packages. The package contains the data sets mentioned in the text (data(package="UsingR")), answers to selected problems (answers()), a few demonstrations (demo()), the errata (errata()), and sample code from the text. The topics of this text line up closely with traditional teaching progression; however, the book also highlights computer-intensive approaches to motivate the more traditional approach. The authors emphasize realistic data and examples and rely on visualization techniques to gather insight. They introduce statistics and R seamlessly, giving students the tools they need to use R and the information they need to navigate the sometimes complex world of statistical computing.
Author: Robert Gould Publisher: ISBN: 9780321823656 Category : Statistics Languages : en Pages : 736
Book Description
We live in a data-driven world, and the goal of this Canadian text is to teach students how to access and analyze these data critically. Canadian authors Jim Stallard and Michelle Boué emphasize that learning statistics extends beyond the classroom to an essential life skill, and want Canadian students to develop a "data habit of mind." Regardless of their math backgrounds, students will learn how to think about data and how to reason using data. With a clear, unintimidating writing style and carefully chosen pedagogy, this text makes data analysis accessible to all students. KEY TOPICS: Introduction to Data; Picturing Variation with Graphs; Numerical Summaries of Centre and Variation; Regression Analysis: Exploring Associations between Variables; Modelling Variation with Probability; Modeling Random Events: The Normal and Binomial Models; Survey Sampling and Inference; Hypothesis Testing for Population Proportions; Inferring Population Means; Associations between Categorical Variables; Multiple Comparisons and Analysis of Variance; Experimental Design: Controlling Variation; Inference without Normality;Inference for Regression MARKET: A textbook suitable for all introductory statistics courses
Author: Herschel Knapp Publisher: SAGE Publications ISBN: 1483313107 Category : Social Science Languages : en Pages : 457
Book Description
Introductory Statistics Using SPSS, by Herschel Knapp, shows readers how to properly select, process, and interpret statistics without heavy emphasis on theory, formula derivations, or abstract mathematical concepts. Each chapter is structured to answer questions that readers most want answered, including: how to choose the appropriate test for each situation, how to set up the data, how to run the test, and how to interpret and document the results. Requiring no hand calculations, this highly applied book helps readers “get the story” from their data. They learn by doing, completing practice exercises at the end of each chapter. Video tutorials on the accompanying website clearly demonstrate how to set up the data and run the test in SPSS. Contents: PART I: STATISTICAL PRINCIPLES – 1) Research Principles 2) Sampling 3) Working in SPSS; PART II: STATISTICAL PROCESSES – 4) Descriptive Statistics 5) T Test 6) ANOVA 7) Paired T Test 8) Correlation and Regression 9) Chi-Square; PART III: DATA HANDLING – 10) Supplemental SPSS Operations; PART IV – SOLUTIONS TO ODD-NUMBERED EXERCISES
Author: Gareth James Publisher: Springer Nature ISBN: 3031387473 Category : Mathematics Languages : en Pages : 617
Book Description
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.
Author: Steve McKillup Publisher: Cambridge University Press ISBN: 1139502948 Category : Medical Languages : en Pages : 430
Book Description
An understanding of statistics and experimental design is essential for life science studies, but many students lack a mathematical background and some even dread taking an introductory statistics course. Using a refreshingly clear and encouraging reader-friendly approach, this book helps students understand how to choose, carry out, interpret and report the results of complex statistical analyses, critically evaluate the design of experiments and proceed to more advanced material. Taking a straightforward conceptual approach, it is specifically designed to foster understanding, demystify difficult concepts and encourage the unsure. Even complex topics are explained clearly, using a pictorial approach with a minimum of formulae and terminology. Examples of tests included throughout are kept simple by using small data sets. In addition, end-of-chapter exercises, new to this edition, allow self-testing. Handy diagnostic tables help students choose the right test for their work and remain a useful refresher tool for postgraduates.
Author: Barbara Illowsky Publisher: Createspace Independent Publishing Platform ISBN: 9781508534136 Category : Languages : en Pages : 0
Book Description
Collaborative Stastistics is intended for introductory statistics courses being taken by students at two- and four-year colleges who are majoring in fields other than math or engineering. Intermediate algebra is the only prerequisite. The book focuses on applications of statistical knowledge rather than the theory behind it. Barbara Illowsky and Susan Dean are professors of mathematics and statistics at De Anza College in Cupertino, CA. They present nationally on integrating technology, distance learning, collaborative learning, and multiculturalism into the elementary statistics classroom.
Author: Barbara Illowsky
Author: Barbara Illowsky
Author: Alexander Holmes
Author: Peter Dalgaard
Author: John Verzani
Author: Stephen Kokoska
Author: Robert Gould
Author: Herschel Knapp
Author: Gareth James
Author: Steve McKillup
Author: Barbara Illowsky