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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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Teachers Resource Binder to accompany Statistics through Applications. Please see main text ISBN 0716747723 for further details.

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Genre:
Author: Dan Yates
Publisher:
Release: 2004-03
File: 100 Pages
ISBN-13: 0716712628

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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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This volume provides an overview of existing methodology, together with details of new theoretical developments and some practical applications.

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Genre: Technology & Engineering
Author: Jorge Mateu
Publisher: Wit Pr/Computational Mechanics
Release: 2002-01
File: 345 Pages
ISBN-13: 1853126497

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Printed Test Bank to accompany Statistics Through Applications. Please see main text ISBN 0716747723 for further details.

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Genre: Nuclear energy
Author: Dan Yates
Publisher:
Release: 2004-03
File: 50 Pages
ISBN-13: 0716712482

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Foundations and Applications of Statistics simultaneously emphasizes both the foundational and the computational aspects of modern statistics. Engaging and accessible, this book is useful to undergraduate students with a wide range of backgrounds and career goals. The exposition immediately begins with statistics, presenting concepts and results from probability along the way. Hypothesis testing is introduced very early, and the motivation for several probability distributions comes from p-value computations. Pruim develops the students' practical statistical reasoning through explicit examples and through numerical and graphical summaries of data that allow intuitive inferences before introducing the formal machinery. The topics have been selected to reflect the current practice in statistics, where computation is an indispensible tool. In this vein, the statistical computing environment R is used throughout the text and is integral to the exposition. Attention is paid to developing students' mathematical and computational skills as well as their statistical reasoning. Linear models, such as regression and ANOVA, are treated with explicit reference to the underlying linear algebra, which is motivated geometrically. Foundations and Applications of Statistics discusses both the mathematical theory underlying statistics and practical applications that make it a powerful tool across disciplines. The book contains ample material for a two-semester course in undergraduate probability and statistics. A one-semester course based on the book will cover hypothesis testing and confidence intervals for the most common situations. In the second edition, the R code has been updated throughout to take advantage of new R packages and to illustrate better coding style. New sections have been added covering bootstrap methods, multinomial and multivariate normal distributions, the delta method, numerical methods for Bayesian inference, and nonlinear least squares. Also, the use of matrix algebra has been expanded, but remains optional, providing instructors with more options regarding the amount of linear algebra required.

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Genre: Mathematical statistics
Author: Randall Pruim
Publisher: American Mathematical Soc.
Release: 2018-04-04
File: 820 Pages
ISBN-13: 9781470428488

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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: 2011-12-07
File: 845 Pages
ISBN-13: 9781461403913

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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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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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