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Watch a video introduction here. Statistics Through Applications (STA) is the only text written specifically for high school statistics course. Designed to be read, the book takes a data analysis approach that emphasizes conceptual understanding over computation, while recognizing that some computation is necessary. The focus is on the statistical thinking behind data gathering and interpretation. The high school statistics course is often the first applied math course students take. STA engages students in learning how statisticians contribute to our understanding of the world and helps students to become more discerning consumers of the statistics they encounter in ads, economic reports, political campaigns, and elsewhere. New and improved! STA 2e features expanded coverage of probability, a reorganized presentation of data analysis, a new color design and much more. Please see the posted sample chapter or request a copy today to see for yourself.

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Genre: Mathematics
Author: Daren S. Starnes
Publisher: Macmillan
Release: 2009-12-25
File: 600 Pages
ISBN-13: 9781429219747

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The NCTM urges the study of statistics in high school, and many schools have designed courses based on these NCTM recommendations. Now from the authors of the overwhelming favorite for the AP Statistics course (The Practice of Statistics) comes the first text written exclusively for a non-AP level high introduction to statistics for high school students. Statistics Through Applications is the ideal alternative for juniors and seniors not going into high level courses such as calculus, but who are interested in an introduction to the important topics of statistics. The book's data analysis approach moves students away from monotonous computation to focus on the statistical thinking behind data gathering and interpretation. This approach more accurately reflects the way working statisticians contribute to our understanding of the world. It also helps students be more discerning consumers of statistics, teaching them to look closely at what the numbers from surveys, election polls, and medical studies are really saying. State Correlationshttp://www.bfwpub.com/pdfs/yatessta/state.htm

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Genre: Computers
Author: Dan Yates
Publisher: Macmillan
Release: 2004-03
File: 600 Pages
ISBN-13: 0716747723

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Integrating the theory and practice of statistics through a series of case studies, each lab introduces a problem, provides some scientific background, suggests investigations for the data, and provides a summary of the theory used in each case. Aimed at upper-division students.

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Genre: Mathematics
Author: Deborah Nolan
Publisher: Springer Science & Business Media
Release: 2006-05-02
File: 283 Pages
ISBN-13: 9780387227436

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The purpose of this volume is to provide an overview of Terry Speed’s contributions to statistics and beyond. Each of the fifteen chapters concerns a particular area of research and consists of a commentary by a subject-matter expert and selection of representative papers. The chapters, organized more or less chronologically in terms of Terry’s career, encompass a wide variety of mathematical and statistical domains, along with their application to biology and medicine. Accordingly, earlier chapters tend to be more theoretical, covering some algebra and probability theory, while later chapters concern more recent work in genetics and genomics. The chapters also span continents and generations, as they present research done over four decades, while crisscrossing the globe. The commentaries provide insight into Terry’s contributions to a particular area of research, by summarizing his work and describing its historical and scientific context, motivation, and impact. In addition to shedding light on Terry’s scientific achievements, the commentaries reveal endearing aspects of his personality, such as his intellectual curiosity, energy, humor, and generosity.

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Genre: Mathematics
Author: Sandrine Dudoit
Publisher: Springer Science & Business Media
Release: 2012-04-11
File: 665 Pages
ISBN-13: 9781461413462

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Students in the sciences, economics, psychology, social sciences, and medicine take introductory statistics. Statistics is increasingly offered at the high school level as well. However, statistics can be notoriously difficult to teach as it is seen by many students as difficult and boring, if not irrelevant to their subject of choice. To help dispel these misconceptions, Gelman and Nolan have put together this fascinating and thought-provoking book. Based on years of teaching experiencethe book provides a wealth of demonstrations, examples and projects that involve active student participation. Part I of the book presents a large selection of activities for introductory statistics courses and combines chapters such as, 'First week of class', with exercises to break the ice and get students talking; then 'Descriptive statistics' , collecting and displaying data; then follows the traditional topics - linear regression, data collection, probability and inference. Part IIgives tips on what does and what doesn't work in class: how to set up effective demonstrations and examples, how to encourage students to participate in class and work effectively in group projects. A sample course plan is provided. Part III presents material for more advanced courses on topics such as decision theory, Bayesian statistics and sampling.

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Genre: Education
Author: Andrew Gelman
Publisher: Oxford University Press
Release: 2002
File: 299 Pages
ISBN-13: 9780198572251

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Many mathematical statistics texts are heavily oriented toward a rigorous mathematical development of probability and statistics, without much attention paid to how statistics is actually used.. In contrast, Modern Mathematical Statistics with Applications, Second Edition strikes a balance between mathematical foundations and statistical practice. In keeping with the recommendation that every math student should study statistics and probability with an emphasis on data analysis, accomplished authors Jay Devore and Kenneth Berk make statistical concepts and methods clear and relevant through careful explanations and a broad range of applications involving real data. The main focus of the book is on presenting and illustrating methods of inferential statistics that are useful in research. It begins with a chapter on descriptive statistics that immediately exposes the reader to real data. The next six chapters develop the probability material that bridges the gap between descriptive and inferential statistics. Point estimation, inferences based on statistical intervals, and hypothesis testing are then introduced in the next three chapters. The remainder of the book explores the use of this methodology in a variety of more complex settings. This edition includes a plethora of new exercises, a number of which are similar to what would be encountered on the actuarial exams that cover probability and statistics. Representative applications include investigating whether the average tip percentage in a particular restaurant exceeds the standard 15%, considering whether the flavor and aroma of Champagne are affected by bottle temperature or type of pour, modeling the relationship between college graduation rate and average SAT score, and assessing the likelihood of O-ring failure in space shuttle launches as related to launch temperature.

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Genre: Mathematics
Author: Jay L. Devore
Publisher: Springer Science & Business Media
Release: 2011-12-06
File: 845 Pages
ISBN-13: 9781461403906

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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 to marketing to 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, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

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Genre: Mathematics
Author: Gareth James
Publisher: Springer Science & Business Media
Release: 2013-06-24
File: 426 Pages
ISBN-13: 9781461471387

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Mathematical Statistics with Applications in R, Second Edition, offers a modern calculus-based theoretical introduction to mathematical statistics and applications. The book covers many modern statistical computational and simulation concepts that are not covered in other texts, such as the Jackknife, bootstrap methods, the EM algorithms, and Markov chain Monte Carlo (MCMC) methods such as the Metropolis algorithm, Metropolis-Hastings algorithm and the Gibbs sampler. By combining the discussion on the theory of statistics with a wealth of real-world applications, the book helps students to approach statistical problem solving in a logical manner. This book provides a step-by-step procedure to solve real problems, making the topic more accessible. It includes goodness of fit methods to identify the probability distribution that characterizes the probabilistic behavior or a given set of data. Exercises as well as practical, real-world chapter projects are included, and each chapter has an optional section on using Minitab, SPSS and SAS commands. The text also boasts a wide array of coverage of ANOVA, nonparametric, MCMC, Bayesian and empirical methods; solutions to selected problems; data sets; and an image bank for students. Advanced undergraduate and graduate students taking a one or two semester mathematical statistics course will find this book extremely useful in their studies. Step-by-step procedure to solve real problems, making the topic more accessible Exercises blend theory and modern applications Practical, real-world chapter projects Provides an optional section in each chapter on using Minitab, SPSS and SAS commands Wide array of coverage of ANOVA, Nonparametric, MCMC, Bayesian and empirical methods

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Genre: Mathematics
Author: Kandethody M. Ramachandran
Publisher: Elsevier
Release: 2014-09-14
File: 826 Pages
ISBN-13: 9780124171329

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In their bestselling MATHEMATICAL STATISTICS WITH APPLICATIONS, premiere authors Dennis Wackerly, William Mendenhall, and Richard L. Scheaffer present a solid foundation in statistical theory while conveying the relevance and importance of the theory in solving practical problems in the real world. The authors’ use of practical applications and excellent exercises helps students discover the nature of statistics and understand its essential role in scientific research. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

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Genre: Mathematics
Author: Dennis Wackerly
Publisher: Nelson Education
Release: 2007-10-10
File: 944 Pages
ISBN-13: 9781111798789

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This text teaches maths in a step-by-step fashion – ideal for students on first-year engineering and pre-degree courses. - Hundreds of examples and exercises, the majority set in an applied engineering context so that you immediately see the purpose of what you are learning - Introductory chapter revises indices, fractions, decimals, percentages and ratios - Fully worked solutions to every problem on the companion website at www.palgrave.com/engineering/singh plus searchable glossary, e-index, extra exercises, extra content and more!

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Genre: Mathematics
Author: Kuldeep Singh
Publisher: Macmillan International Higher Education
Release: 2011-07-26
File: 944 Pages
ISBN-13: 9780230345980

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