R is the world's most popular language for developing statistical software: Archaeologists use it to track the spread of ancient …
Solve real-world data problems with R and machine learning Key Features Third edition of the bestselling, widely acclaimed R machine …
Much of the data available today is unstructured and text-heavy, making it challenging for analysts to apply their usual data …
Based on the author’s experience in teaching data science for more than 10 years, Mathematics and Programming for Machine Learning …
There is an explosion of interest in Bayesian statistics, primarily because recently created computational methods have finally made Bayesian analysis …
R has been the gold standard in applied machine learning for a long time. Surveys show that it is the …
Get an introduction to functional data structures using R and write more effective code and gain performance for your programs. …
This advanced textbook for business statistics teaches, statistical analyses and research methods utilizing business case studies and financial data with …
This advanced textbook for business statistics teaches, statistical analyses and research methods utilizing business case studies and financial data, with …
AnnotationCustomer and Business Analytics: Applied Data Mining for Business Decision Making Using R explains and demonstrates, via the accompanying open-source …
Big data analytics is the process of examining large amounts of data of a variety of types to uncover hidden …
This easy-to-follow guide provides R and Python recipes to help you learn and apply the top languages in the field …
Designed as a textbook for a one or two-term introduction to mathematical statistics for students training to become data scientists, …
The majority of data sets collected by researchers in all disciplines are multivariate, meaning that several measurements, observations, or recordings …
This book is based on over a dozen years teaching a Bayesian Statistics course. The material presented here has been …
Stress Testing and Risk Integration in Banks provides a comprehensive view of the risk management activity by means of the …
Now, a leader of Northwestern University's prestigious analytics program presents a fully-integrated treatment of both the business and academic elements …
This text grew out of the author’s notes for a course that he has taught for many years to a …
This text emphasizes nonlinear models for a course in time series analysis. After introducing stochastic processes, Markov chains, Poisson processes, …
This book is the revised and extended second edition of Statistics for Linguistics with R. The comprehensive revision includes new …
This is the third, newly revised and extended edition of this successful book (that has already been translated into three …
Neil J. Salkind’s bestselling Statistics for People Who (Think They) Hate Statistics has been helping ease student anxiety around an …
A Practical Guide to Implementing Nonparametric and Rank-Based Procedures Nonparametric Statistical Methods Using R covers traditional nonparametric methods and rank-based …
The first textbook of its kind, Quantitative Corpus Linguistics with R demonstrates how to use the open source programming language …
This textbook examines empirical linguistics from a theoretical linguist’s perspective. It provides both a theoretical discussion of what quantitative corpus …
A Guide to Doing Statistics in Second Language Research Using SPSS and R, Second Edition is the only text available …
