Data Mining for Business Analytics

Data Mining for Business Analytics is used at over 560 universities and colleges, and has been translated into Korean and Chinese. It has been adapted for four software environments (R, Python, Excel and JMP) and, since it was first published in 2007, has been through 11 editions.

Introductory Statistics and Analytics: A Resampling Perspective

Introductory Statistics and Analytics: A Resampling Perspective provides an accessible approach to statistical analytics, resampling, and the bootstrap for readers at multiple levels of exposure to basic probability and statistics.

Practical Statistics for Data Scientists: 50 Essential Concepts

Statistical methods are a key part of data science, yet few data scientists have formal statistical training. Courses and books on basic statistics rarely cover the topic from a data science perspective.

Practical Statistics explains how to apply key statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what’s important and what’s not.

Creating A Predictive Modeling Framework

A global humanitarian organization asked Elder Research to develop a customized training and collaborative modeling framework. 

Uplift Modeling: Making Predictive Models Actionable

The Generalization Paradox of Ensembles

Netflix, Dark Knowledge, and Why Simpler Can Be Better

It is a Mistake to Answer Every Inquiry

Charlie Batch and the Cost of Obfuscation

Be a Data Detective

Haystacks and Needles Anomaly Detection

It is a Mistake to Listen Only to the Data

It Is a Mistake to Extrapolate

It is a Mistake to Discount Pesky Cases

It is a Mistake to Accept Leaks from the Future

Evaluate the Validity of Your Discovery with Target Shuffling White Paper

The Ten Most Common Data Science Business Mistakes

Practical Text Mining – Applying Analytics and Modeling

In one comprehensive resource, Practical Text Mining and Statistical Analysis for Non-Structured Text Data Applications provides complete coverage of statistical and analytical concepts, techniques, and applications for text mining.

Handbook of Statistical Analysis and Data Mining Applications

The Handbook of Statistical Analysis and Data Mining Applications is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers (both academic and industrial) through all stages of data analysis, model building and implementation.

It is a Mistake to Rely on One Technique