Modeling techniques in predictive analytics with python and R : a guide to data science / Thomas W. Miller.

Includes bibliographical references and index.

1 Analytics and Data Science
2 Advertising and Promotion
3 Preference and Choice
4 Market Basket Analysis
5 Economic Data Analysis
6 Operations Management
7 Text Analytics
8 Sentiment Analysis
9 Sports Analytics
10 Spatial Data Analysis
11 Brand and Price
12 The Big Little Data Game

A Data Science Methods
A.1 Databases and Data Preparation
A.2 Classical and Bayesian Statistics
A.3 Regression and Classification
A.4 Machine Learning
A.5 Web and Social Network Analysis
A.6 Recommender Systems
A.7 Product Positioning
A.8 Market Segmentation
A.9 Site Selection
A.10 Financial Data Science

B Measurement
C Case Studies
C.1 Return of the Bobbleheads
C.2 DriveTime Sedans
C.3 Two Month's Salary
C.4 Wisconsin Dells
C.5 Computer Choice Study

D Code and Utilities
Bibliography
Index.

This book could be for an introductory course in Analytics discussing what is Analytics and what are some example applications.