Descriptive Analyses - Describe a set of data. E.g., census data, Google NGram viewer

Exploratory Analyses - Finding relationships you didn’t know about. Should not be used for generalizing or prediction.

Inferential Analyses - Use a relatively small sample of data to infer for bigger population.

Predictive Analyses - To use the data on some objects to predict values for another object.

Causal Analyses -

Bibliography

Books

R in a Nutshell - A quick and practical reference to learn what is becoming the standard for developing statistical software.
* Statistics in a Nutshell - An introduction and reference for anyone with no previous background in statistics.
* Data Analysis with Open Source Tools - This book shows you how to think about data and the results you want to achieve with it.
* Programming Collective Intelligence - Learn how to build web applications that mine the data created by people on the Internet.
* Beautiful Data - Learn from the best data practitioners in the field about how wide-ranging — and beautiful — working with data can be.
* Beautiful Visualization - This book demonstrates why visualizations are beautiful not only for their aesthetic design, but also for elegant layers of detail.
* Head First Statistics - This book teaches statistics through puzzles, stories, visual aids, and real-world examples.
* Head First Data Analysis - Learn how to collect your data, sort the distractions from the truth, and find meaningful patterns.