Introductory Statistics Preliminary Edition
Download Introductory Statistics Preliminary Edition full books in PDF, epub, and Kindle. Read online free Introductory Statistics Preliminary Edition ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
| Author | : Stephen Kokoska |
| Publisher | : Macmillan |
| Total Pages | : 1012 |
| Release | : 2008-01-03 |
| Genre | : Mathematics |
| ISBN | : 9780716757627 |
Written to appeal to students and instructors who appreciate statistics for its precision and logic, Introductory Statistics: A Problem-Solving Approach helps students learn statistical concepts by using a stepped problem-solving approach. After completing an introductory statistics course with this textbook, students should understand the process of basic statistical arguments. They should grasp the importance of assumptions and be able to follow valid arguments or identify inaccurate conclusions. Most importantly, they should understand the process of statistical inference. The philosophy of this text is simple: statistics is often hard for students, and in order to understand concepts, the material must be presented in an orderly, precise, friendly manner. It must be easy to read and follow, and there must be numerous examples and exercises. The text aims to be easy-to-read, down-to-earth, systematic, and methodical. Each new idea builds upon concepts presented earlier. A touch of humor is important, especially for many students who are afraid of, and even dislike, mathematics and statistics.
| Author | : David Diez |
| Publisher | : |
| Total Pages | : |
| Release | : 2015-07-02 |
| Genre | : |
| ISBN | : 9781943450046 |
The OpenIntro project was founded in 2009 to improve the quality and availability of education by producing exceptional books and teaching tools that are free to use and easy to modify. We feature real data whenever possible, and files for the entire textbook are freely available at openintro.org. Visit our website, openintro.org. We provide free videos, statistical software labs, lecture slides, course management tools, and many other helpful resources.
| Author | : Nathan Tintle |
| Publisher | : Wiley Global Education |
| Total Pages | : 699 |
| Release | : 2015-12-17 |
| Genre | : Mathematics |
| ISBN | : 1119154316 |
Introduction to Statistical Investigations leads students to learn about the process of conducting statistical investigations from data collection, to exploring data, to statistical inference, to drawing appropriate conclusions. The text is designed for a one-semester introductory statistics course. It focuses on genuine research studies, active learning, and effective use of technology. Simulations and randomization tests introduce statistical inference, yielding a strong conceptual foundation that bridges students to theory-based inference approaches. Repetition allows students to see the logic and scope of inference. This implementation follows the GAISE recommendations endorsed by the American Statistical Association.
| Author | : Richard DeVeaux |
| Publisher | : Addison Wesley Publishing Company |
| Total Pages | : 580 |
| Release | : 2002-07-15 |
| Genre | : Mathematics |
| ISBN | : 9780321109354 |
| Author | : Peter C. Bruce |
| Publisher | : John Wiley & Sons |
| Total Pages | : 320 |
| Release | : 2015-01-08 |
| Genre | : Mathematics |
| ISBN | : 1118881338 |
Concise, thoroughly class-tested primer that features basic statistical concepts in the concepts in the context of analytics, resampling, and the bootstrap A uniquely developed presentation of key statistical topics, Introductory Statistics and Analytics: A Resampling Perspective provides an accessible approach to statistical analytics, resampling, and the bootstrap for readers with various levels of exposure to basic probability and statistics. Originally class-tested at one of the first online learning companies in the discipline, www.statistics.com, the book primarily focuses on applications of statistical concepts developed via resampling, with a background discussion of mathematical theory. This feature stresses statistical literacy and understanding, which demonstrates the fundamental basis for statistical inference and demystifies traditional formulas. The book begins with illustrations that have the essential statistical topics interwoven throughout before moving on to demonstrate the proper design of studies. Meeting all of the Guidelines for Assessment and Instruction in Statistics Education (GAISE) requirements for an introductory statistics course, Introductory Statistics and Analytics: A Resampling Perspective also includes: Over 300 “Try It Yourself” exercises and intermittent practice questions, which challenge readers at multiple levels to investigate and explore key statistical concepts Numerous interactive links designed to provide solutions to exercises and further information on crucial concepts Linkages that connect statistics to the rapidly growing field of data science Multiple discussions of various software systems, such as Microsoft Office Excel®, StatCrunch, and R, to develop and analyze data Areas of concern and/or contrasting points-of-view indicated through the use of “Caution” icons Introductory Statistics and Analytics: A Resampling Perspective is an excellent primary textbook for courses in preliminary statistics as well as a supplement for courses in upper-level statistics and related fields, such as biostatistics and econometrics. The book is also a general reference for readers interested in revisiting the value of statistics.
| Author | : Stephen Kokoska |
| Publisher | : W.H. Freeman |
| Total Pages | : 468 |
| Release | : 2005-06-01 |
| Genre | : Mathematics |
| ISBN | : 9780716773856 |
| Author | : Larry Wasserman |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 446 |
| Release | : 2013-12-11 |
| Genre | : Mathematics |
| ISBN | : 0387217363 |
Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.
| Author | : John Verzani |
| Publisher | : CRC Press |
| Total Pages | : 522 |
| Release | : 2018-10-03 |
| Genre | : Computers |
| ISBN | : 1315360306 |
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 | : MINE. ETINKAYA-RUNDEL |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2024 |
| Genre | : |
| ISBN | : 9781943450275 |
| Author | : G. Jay Kerns |
| Publisher | : Lulu.com |
| Total Pages | : 388 |
| Release | : 2010-01-10 |
| Genre | : Education |
| ISBN | : 0557249791 |
This is a textbook for an undergraduate course in probability and statistics. The approximate prerequisites are two or three semesters of calculus and some linear algebra. Students attending the class include mathematics, engineering, and computer science majors.
