Category : Mathematics
Editor : Wiley Global Education
ISBN : 9781119163725
Type : PDF, Epub and Kindle
Language : en
Views : 590
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With Wiley’s Enhanced E-Text, you get all the benefits of a downloadable, reflowable eBook with added resources to make your study time more effective, including: • Embedded & Searchable Tables & Figures • Links to Datasets through wiley.com • Video Solutions & Tutorials • Dataset Index embedded including links to datasets by page number Statistics: Unlocking the Power of Data, 2nd Edition continues to utilize these intuitive methods like randomization and bootstrap intervals to introduce the fundamental idea of statistical inference. These methods are brought to life through authentically relevant examples, enabled through easy to use statistical software, and are accessible at very early stages of a course. The program includes the more traditional methods like t-tests, chi-square texts, etc. but only after students have developed a strong intuitive understanding of inference through randomization methods. The focus throughout is on data analysis and the primary goal is to enable students to effectively collect data, analyze data, and interpret conclusions drawn from data. The program is driven by real data and real applications.

Category : Mathematics
Editor : Wiley Global Education
ISBN : 9781119715894
Type : PDF, Epub and Kindle
Language : en
Views : 807
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Statistics: Unlocking the Power of Data, 2nd Edition continues to utilize these intuitive methods like randomization and bootstrap intervals to introduce the fundamental idea of statistical inference. These methods are brought to life through authentically relevant examples and are accessible at very early stages of the text. Applications are drawn from a wide variety of disciplines, chosen primarily on the basis of perceived interest to students and instructors. Problems and exercises are plentiful and span a wide range of difficulty levels, from very straightforward short answer problems to extended projects.

Category : Mathematics
Editor : John Wiley & Sons
ISBN : 9781119682165
Type : PDF, Epub and Kindle
Language : en
Views : 866
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Statistics: Unlocking the Power of Data, 3rd Edition is designed for an introductory statistics course focusing on data analysis with real-world applications. Students use simulation methods to effectively collect, analyze, and interpret data to draw conclusions. Randomization and bootstrap interval methods introduce the fundamentals of statistical inference, bringing concepts to life through authentically relevant examples. More traditional methods like t-tests, chi-square tests, etc. are introduced after students have developed a strong intuitive understanding of inference through randomization methods. While any popular statistical software package may be used, the authors have created StatKey to perform simulations using data sets and examples from the text. A variety of videos, activities, and a modular chapter on probability are adaptable to many classroom formats and approaches.

Category : Health & Fitness
Editor : Simon and Schuster
ISBN : 9781501144318
Type : PDF, Epub and Kindle
Language : en
Views : 368
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"Sleep is one of the most important but least understood aspects of our life, wellness, and longevity ... An explosion of scientific discoveries in the last twenty years has shed new light on this fundamental aspect of our lives. Now ... neuroscientist and sleep expert Matthew Walker gives us a new understanding of the vital importance of sleep and dreaming"--Amazon.com.

Category : Mathematics
Editor : Wiley
ISBN : 1119309506
Type : PDF, Epub and Kindle
Language : en
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Category : Mathematics
Editor : Springer Science & Business Media
ISBN : 9780387217369
Type : PDF, Epub and Kindle
Language : en
Views : 442
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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.

Category : Computers
Editor : "O'Reilly Media, Inc."
ISBN : 9781491952917
Type : PDF, Epub and Kindle
Language : en
Views : 395
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Statistical methods are a key part of of data science, yet very few data scientists have any formal statistics training. Courses and books on basic statistics rarely cover the topic from a data science perspective. This practical guide explains how to apply various statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you’re familiar with the R programming language, and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you’ll learn: Why exploratory data analysis is a key preliminary step in data science How random sampling can reduce bias and yield a higher quality dataset, even with big data How the principles of experimental design yield definitive answers to questions How to use regression to estimate outcomes and detect anomalies Key classification techniques for predicting which categories a record belongs to Statistical machine learning methods that “learn” from data Unsupervised learning methods for extracting meaning from unlabeled data

Category : Mathematics
Editor : CRC Press
ISBN : 9781315362618
Type : PDF, Epub and Kindle
Language : en
Views : 488
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Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds readers’ knowledge of and confidence in statistical modeling. Reflecting the need for even minor programming in today’s model-based statistics, the book pushes readers to perform step-by-step calculations that are usually automated. This unique computational approach ensures that readers understand enough of the details to make reasonable choices and interpretations in their own modeling work. The text presents generalized linear multilevel models from a Bayesian perspective, relying on a simple logical interpretation of Bayesian probability and maximum entropy. It covers from the basics of regression to multilevel models. The author also discusses measurement error, missing data, and Gaussian process models for spatial and network autocorrelation. By using complete R code examples throughout, this book provides a practical foundation for performing statistical inference. Designed for both PhD students and seasoned professionals in the natural and social sciences, it prepares them for more advanced or specialized statistical modeling. Web Resource The book is accompanied by an R package (rethinking) that is available on the author’s website and GitHub. The two core functions (map and map2stan) of this package allow a variety of statistical models to be constructed from standard model formulas.

Category : Computers
Editor : Cambridge University Press
ISBN : 0521835402
Type : PDF, Epub and Kindle
Language : en
Views : 372
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"This textbook is designed to accompany a one- or two-semester course for advanced undergraduates or beginning graduate students in computer science and applied mathematics. - It gives an excellent introduction to the probabilistic techniques and paradigms used in the development of probabilistic algorithms and analyses. - It assumes only an elementary background in discrete mathematics and gives a rigorous yet accessible treatment of the material, with numerous examples and applications."--Jacket.

Category : Mathematics
Editor : Wiley
ISBN : 1119315573
Type : PDF, Epub and Kindle
Language : en
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Statistics, 2nd Edition moves the curriculum in innovative ways while still looking relatively familiar. Statistics, 2e utilizes intuitive methods to introduce the fundamental idea of statistical inference. These intuitive methods are enabled through statistical software and are accessible at very early stages of a course. The text also includes the more traditional methods such as t-tests, chi-square tests, etc., but only after students have developed a strong intuitive understanding of inference through randomization methods. The text is designed for use in a one-semester introductory statistics course. The focus throughout is on data analysis and the primary goal is to enable students to effectively collect data, analyze data, and interpret conclusions drawn from data. The text is driven by real data and real applications. Students completing the course should be able to accurately interpret statistical results and to analyze straightforward data sets.