Statistics

Statistical Theory & Methods

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Modern Data Science with R

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Benjamin S. Baumer, Daniel T. Kaplan, Nicholas J. Horton
February 2, 2017

Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world problems with data. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical programmi...

Applied Time Series Analysis with R, Second Edition

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Wayne A. Woodward, Henry L. Gray, Alan C. Elliott
December 20, 2016

Virtually any random process developing chronologically can be viewed as a time series. In economics closing prices of stocks, the cost of money, the jobless rate, and retail sales are just a few examples of many. Developed from course notes and extensively classroom-tested, Applied Time Series Anal...

Testing R Code

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Richard Cotton
January 19, 2017

Learn how to write R code with fewer bugs. The problem with programming is that you are always one typo away from writing something silly. Likewise with data analysis, a small mistake in your model can lead to a big mistake in your results. Combining the two disciplines means that it is all too easy...

Change-Point Analysis in Nonstationary Stochastic Models

Boris Brodsky
March 23, 2017

This book covers the development of methods for detection and estimation of changes in complex systems. These systems are generally described by nonstationary stochastic models, which comprise both static and dynamic regimes, linear and nonlinear dynamics, and constant and time-variant structures...

Modern Data Science with R

Benjamin S. Baumer, Daniel T. Kaplan, Nicholas J. Horton
February 02, 2017

Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world problems with data. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical...

Testing R Code

Richard Cotton
January 19, 2017

Learn how to write R code with fewer bugs. The problem with programming is that you are always one typo away from writing something silly. Likewise with data analysis, a small mistake in your model can lead to a big mistake in your results. Combining the two disciplines means that it is all too...

Multilevel Modeling Using Mplus

Holmes Finch, Jocelyn Bolin
December 22, 2016

This book is designed primarily for upper level undergraduate and graduate level students taking a course in multilevel modelling and/or statistical modelling with a large multilevel modelling component. The focus is on presenting the theory and practice of major multilevel modelling...

Handbook of Statistical Methods and Analyses in Sports

Jim Albert, Mark E. Glickman, Tim B. Swartz, Ruud H. Koning
December 21, 2016

This handbook will provide both overviews of statistical methods in sports and in-depth treatment of critical problems and challenges confronting statistical research in sports. The material in the handbook will be organized by major sport (baseball, football, hockey, basketball, and soccer)...

Correspondence Analysis in Practice, Third Edition

Michael Greenacre
December 20, 2016

Drawing on the author’s 45 years of experience in multivariate analysis, Correspondence Analysis in Practice, Third Edition, shows how the versatile method of correspondence analysis (CA) can be used for data visualization in a wide variety of situations. CA and its variants, subset CA, multiple CA...

Applied Time Series Analysis with R, Second Edition

Wayne A. Woodward, Henry L. Gray, Alan C. Elliott
December 20, 2016

Virtually any random process developing chronologically can be viewed as a time series. In economics closing prices of stocks, the cost of money, the jobless rate, and retail sales are just a few examples of many. Developed from course notes and extensively classroom-tested, Applied Time Series...

Multi-State Survival Models for Interval-Censored Data

Ardo van den Hout
December 02, 2016

Multi-State Survival Models for Interval-Censored Data introduces methods to describe stochastic processes that consist of transitions between states over time. It is targeted at researchers in medical statistics, epidemiology, demography, and social statistics. One of the applications in the book...

Small Area Estimation and Microsimulation Modeling

Azizur Rahman, Ann Harding
December 01, 2016

Small Area Estimation and Microsimulation Modeling is the first practical handbook that comprehensively presents modern statistical SAE methods in the framework of ultramodern spatial microsimulation modeling while providing the novel approach of creating synthetic spatial microdata. Along with...

Handbook of Neuroimaging Data Analysis

Hernando Ombao, Martin Lindquist, Wesley Thompson, John Aston
November 14, 2016

This book explores various state-of-the-art aspects behind the statistical analysis of neuroimaging data. It examines the development of novel statistical approaches to model brain data. Designed for researchers in statistics, biostatistics, computer science, cognitive science, computer engineering...

Music Data Analysis: Foundations and Applications

Claus Weihs, Dietmar Jannach, Igor Vatolkin, Guenter Rudolph
November 07, 2016

This book provides a comprehensive overview of music data analysis, from introductory material to advanced concepts. It covers various applications including transcription and segmentation as well as chord and harmony, instrument and tempo recognition. It also discusses the implementation aspects...

Multivariate Statistical Methods: A Primer, Fourth Edition

Bryan F.J. Manly, Jorge A. Navarro Alberto
October 11, 2016

Multivariate Statistical Methods: A Primer provides an introductory overview of multivariate methods without getting too deep into the mathematical details. This fourth edition is a revised and updated version of this bestselling introductory textbook. It retains the clear and concise style of the...

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