Document Type
Book
Date
2013
Keywords
data science, information management, statistics, library science
Language
English
Disciplines
Human Resources Management | Industrial and Organizational Psychology | Library and Information Science | Management Information Systems | Organizational Behavior and Theory
Description/Abstract
In this Introduction to Data Science eBook, a series of data problems of increasing complexity is used to illustrate the skills and capabilities needed by data scientists. The open source data analysis program known as "R" and its graphical user interface companion "R-Studio" are used to work with real data examples to illustrate both the challenges of data science and some of the techniques used to address those challenges. To the greatest extent possible, real datasets reflecting important contemporary issues are used as the basis of the discussions.
Recommended Citation
82. Stanton, J.M. (2012). Introduction to Data Science, Third Edition. iTunes Open Source eBook. Available: https://itunes.apple.com/us/book/introduction-to-data-science/id529088127?mt=11
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.
Included in
Human Resources Management Commons, Industrial and Organizational Psychology Commons, Library and Information Science Commons, Management Information Systems Commons, Organizational Behavior and Theory Commons
Additional Information
The 2013 version is the first version of Introduction to Data Science. It is open-access. If you have questions about it or need an accessible file, please contact us.
The most current version of the text can be found at:
Saltz, J. S., & Stanton, J. M. (2017). An Introduction to Data Science. Thousand Oaks: SAGE Publications.
https://us.sagepub.com/en-us/nam/an-introduction-to-data-science/book256486