Statistics

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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...

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...

Errors, Blunders, and Lies: How to Tell the Difference

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David Salsburg
April 19, 2017

We live in a world that is not quite "right." The central tenet of statistical inquiry is that Observation = Truth + Error because even the most careful of scientific investigations have always been bedeviled by uncertainty. Our attempts to measure things are plagued with small errors. Our attempt...

The Banking Crisis Handbook

Greg N Gregoriou
May 22, 2017

Explores the Origin of the Recent Banking Crisis and how to Preclude Future Crises Shedding new light on the recent worldwide banking debacle, The Banking Crisis Handbook presents possible remedies as to what should have been done prior, during, and after the crisis. With contributions from...

Algorithms for Next-Generation Sequencing

Wing-Kin Sung
May 15, 2017

Advances in sequencing technology have allowed scientists to study the human genome in greater depth and on a larger scale than ever before – as many as hundreds of millions of short reads in the course of a few days. But what are the best ways to deal with this flood of data? Algorithms for...

Statistical Methods for the Study of Undeciphered Lanquages

Ronojoy Adhikari
May 15, 2017

This book presents an overview of the state of the art in the application of unsupervised algorithms to the study of undeciphered scripts. It shows how these algorithms can be applied to the Indus script, which is a major undeciphered script of the ancient world. The author explains how modern...

Introduction to Financial Models for Management and Planning, Second Edition

James R. Morris, John P. Daley
May 15, 2017

A properly structured financial model can provide decision makers with a powerful planning tool that helps them identify the consequences of their decisions before they are put into practice. Introduction to Financial Models for Management and Planning, Second Edition enables professionals and...

Flexible Regression and Smoothing: Using GAMLSS in R

Mikis D. Stasinopoulos, Robert A. Rigby, Gillian Z. Heller, Vlasios Voudouris, Fernanda De Bastiani
May 08, 2017

This book is about learning from data using the Generalized Additive Models for Location, Scale and Shape (GAMLSS). GAMLSS extends the Generalized Linear Models (GLMs) and Generalized Additive Models (GAMs) to accommodate large complex datasets, which are increasingly prevalent. GAMLSS allows any...

Acceptance Sampling in Quality Control,Third Edition

Edward G. Schilling, Dean V. Neubauer
May 03, 2017

Acceptance Sampling in Quality Control, Third Edition presents the state of the art in the methodology of sampling while integrating both theory and best practices. It discusses various standards, including those from the ISO, MIL-STD and ASTM and explores how to set quality levels. The book also...

Clinical Trial Data Analysis Using R and SAS, Second Edition

Ding-Geng (Din) Chen, Karl E. Peace, Pinggao Zhang
May 03, 2017

Review of the First Edition "The goal of this book, as stated by the authors, is to fill the knowledge gap that exists between developed statistical methods and the applications of these methods. Overall, this book achieves the goal successfully and does a nice job. I would highly recommend it …The...

What Makes Variables Random: Probability for the Applied Researcher

Peter J. Veazie
May 03, 2017

What Makes Variables Random: Probability for the Applied Researcher provides an introduction to the foundations of probability that underlie the statistical analyses used in applied research. By explaining probability in terms of measure theory, it gives the applied researchers a conceptual...

Handbook of Methods for Designing, Monitoring, and Analyzing Dose-Finding Trials

John O'Quigley, Alexia Iasonos, Björn Bornkamp
April 26, 2017

Handbook of Methods for Designing, Monitoring, and Analyzing Dose-Finding Trials gives a thorough presentation of state-of-the-art methods for early phase clinical trials. The methodology of clinical trials has advanced greatly over the last 20 years and, arguably, nowhere greater than that of...

Exploratory Multivariate Analysis by Example Using R, Second Edition

Francois Husson, Sebastien Le, Jérôme Pagès
April 25, 2017

Full of real-world case studies and practical advice, Exploratory Multivariate Analysis by Example Using R, Second Edition focuses on four fundamental methods of multivariate exploratory data analysis that are most suitable for applications. It covers principal component analysis (PCA) when...

Equivalence: Elizabeth L. Scott at Berkeley

Amanda L. Golbeck
April 19, 2017

Equivalence: Elizabeth L. Scott at Berkeley is the compelling story of one pioneering statistician’s relentless twenty-year effort to promote the status of women in academe and science. Part biography and part microhistory, the book provides the context and background to understand Scott’s...

Errors, Blunders, and Lies: How to Tell the Difference

David Salsburg
April 19, 2017

We live in a world that is not quite "right." The central tenet of statistical inquiry is that Observation = Truth + Error because even the most careful of scientific investigations have always been bedeviled by uncertainty. Our attempts to measure things are plagued with small errors. Our attempts...

Conferences

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