[PDF] Statistics Through Applications

• Author : Daren S. Starnes,Dan Yates,David S. Moore
• Publisher : Macmillan
• Release Date : 2009-12-25
• ISBN : 9781429219747

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

• Author : Paul H. Kvam,Brani Vidakovic
• Publisher : John Wiley & Sons
• Release Date : 2007-08-24
• ISBN : 0470168692

A thorough and definitive book that fully addresses traditional and modern-day topics of nonparametric statistics This book presents a practical approach to nonparametric statistical analysis and provides comprehensive coverage of both established and newly developed methods. With the use of MATLAB, the authors present information on theorems and rank tests in an applied fashion, with an emphasis on modern methods in regression and curve fitting, bootstrap confidence intervals, splines, wavelets, empirical likelihood, and goodness-of-fit testing. Nonparametric Statistics with Applications to

• Author : Deborah Nolan,Terry P. Speed
• Publisher : Springer Science & Business Media
• Release Date : 2006-05-02
• ISBN : 9780387227436

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.

• Author : Glen McPherson
• Publisher : Springer Science & Business Media
• Release Date : 2013-06-29
• ISBN : 9781475734355

This book describes the basis, application, and interpretation of statistics, and presents a wide range of univariate and multivariate statistical methodology. The Second Edition retains the unique feature of being written from the users' perspective; it connects statistical models and methods to investigative questions and background information, and connects statistical results with interpretations in plain English. In keeping with this approach, methods are grouped by usage rather than by commonality of statistical methodology.

• Author : Larry Wasserman,Larry Alan Wasserman
• Publisher : Springer Science & Business Media
• Release Date : 2004-09-17
• ISBN : 0387402721

This book is for people who want to learn probability and statistics quickly. It brings together many of the main ideas in modern statistics in one place. The book is suitable for students and researchers in statistics, computer science, data mining and machine learning. This book covers a much wider range of topics than a typical introductory text on mathematical statistics. It includes modern topics like nonparametric curve estimation, bootstrapping and classification, topics that are usually relegated to follow-up courses.

• Author : David Ruppert
• Publisher : Springer
• Release Date : 2014-02-26
• ISBN : 9781441968760

This book emphasizes the applications of statistics and probability to finance. The basics of these subjects are reviewed and more advanced topics in statistics, such as regression, ARMA and GARCH models, the bootstrap, and nonparametric regression using splines, are introduced as needed. The book covers the classical methods of finance and it introduces the newer area of behavioral finance. Applications and use of MATLAB and SAS software are stressed. The book will serve as a text in courses aimed at

• Author : Laura M. Chihara,Tim C. Hesterberg
• Publisher : John Wiley & Sons
• Release Date : 2012-09-05
• ISBN : 9781118518953

This book bridges the latest software applications with the benefits of modern resampling techniques Resampling helps students understand the meaning of sampling distributions, sampling variability, P-values, hypothesis tests, and confidence intervals. This groundbreaking book shows how to apply modern resampling techniques to mathematical statistics. Extensively class-tested to ensure an accessible presentation, Mathematical Statistics with Resampling and R utilizes the powerful and flexible computer language R to underscore the significance and benefits of modern resampling techniques. The book begins by introducing

• Author : Peter Whittle
• Publisher : Springer Science & Business Media
• Release Date : 2000-04-20
• ISBN : 0387989552

This book has exerted a continuing appeal since publication of its original edition in 1970. It develops the theory of probability from axioms on the expectation functional rather than on probability measure, demonstrates that the standard theory unrolls more naturally and economically this way, and demonstrates that applications of real interest can be addressed almost immediately. Early analysts of games of chance found the question "What is the fair price for entering this game?" quite as natural as "What is the

• Author : Darlene Renee Goldstein,T. P. Speed
• Publisher : IMS
• Release Date : 2003
• ISBN : 0940600560

• Author : Erich L. Lehmann,Joseph P. Romano
• Publisher : Springer Science & Business Media
• Release Date : 2006-03-30
• ISBN : 9780387276052

The third edition of Testing Statistical Hypotheses updates and expands upon the classic graduate text, emphasizing optimality theory for hypothesis testing and confidence sets. The principal additions include a rigorous treatment of large sample optimality, together with the requisite tools. In addition, an introduction to the theory of resampling methods such as the bootstrap is developed. The sections on multiple testing and goodness of fit testing are expanded. The text is suitable for Ph.D. students in statistics and includes

• Author : Richard M. Heiberger,Burt Holland
• Publisher : Springer Science & Business Media
• Release Date : 2013-06-29
• ISBN : 9781475742848

This presentation of statistical methods features extensive use of graphical displays for exploring data and for displaying the analysis. The authors demonstrate how to analyze data—showing code, graphics, and accompanying computer listings. They emphasize how to construct and interpret graphs, discuss principles of graphical design, and show how tabular results are used to confirm the visual impressions derived from the graphs. Many of the graphical formats are novel and appear here for the first time in print.

• Author : Larry Wasserman
• Publisher : Springer Science & Business Media
• Release Date : 2006-09-10
• ISBN : 9780387306230

This text provides the reader with a single book where they can find accounts of a number of up-to-date issues in nonparametric inference. The book is aimed at Masters or PhD level students in statistics, computer science, and engineering. It is also suitable for researchers who want to get up to speed quickly on modern nonparametric methods. It covers a wide range of topics including the bootstrap, the nonparametric delta method, nonparametric regression, density estimation, orthogonal function methods, minimax estimation,

• Author : Charles S. Davis
• Publisher : Springer Science & Business Media
• Release Date : 2008-01-10
• ISBN : 9780387215730

A comprehensive introduction to a wide variety of statistical methods for the analysis of repeated measurements. It is designed to be both a useful reference for practitioners and a textbook for a graduate-level course focused on methods for the analysis of repeated measurements. The important features of this book include a comprehensive coverage of classical and recent methods for continuous and categorical outcome variables; numerous homework problems at the end of each chapter; and the extensive use of real data

• Author : Prabhanjan N. Tattar,Suresh Ramaiah,B. G. Manjunath
• Publisher : John Wiley & Sons
• Release Date : 2016-03-15
• ISBN : 9781119152736

Integrates the theory and applications of statistics using R A Course in Statistics with R has been written to bridge the gap between theory and applications and explain how mathematical expressions are converted into R programs. The book has been primarily designed as a useful companion for a Masters student during each semester of the course, but will also help applied statisticians in revisiting the underpinnings of the subject. With this dual goal in mind, the book begins with R

• Author : Jianqing Fan,Jianxin Pan
• Publisher : Springer Nature
• Release Date : 2020-05-22
• ISBN : 9783030461614

The collection and analysis of data play an important role in many fields of science and technology, such as computational biology, quantitative finance, information engineering, machine learning, neuroscience, medicine, and the social sciences. Especially in the era of big data, researchers can easily collect data characterised by massive dimensions and complexity. In celebration of Professor Kai-Tai Fang’s 80th birthday, we present this book, which furthers new and exciting developments in modern statistical theories, methods and applications. The book features