The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
A Conceptual and Pragmatic Review of Regression Analysis for Predictive Analytics
Abstract
Regression analysis and modeling are powerful predictive analytical tools for knowledge discovery through examining and capturing the complex hidden relationships and patterns among the quantitative variables. Regression analysis is widely used to: (a) collect massive amounts of organizational performance data such as Web server logs and sales transactions. Such data is referred to as “Big Data”; and (b) improve transformation of massive data into intelligent information (knowledge) by discovering trends and patterns in unknown hidden relationships. The intelligent information can then be used to make informed data-based predictions of future organizational outcomes such as organizational productivity and performance using predictive analytics such as regression analysis methods. The main purpose of this chapter is to present a conceptual and practical overview of simple- and multiple- linear regression analyses.
Related Content
N. Geethanjali, K. M. Ashifa, Avantika Raina, Jayashree Patil, Rameshwaran Byloppilly, S. Suman Rajest.
© 2024.
19 pages.
|
Praveen Kakada, Muhammed Shafi M. K..
© 2024.
14 pages.
|
P. S. Venkateswaran, Divya Marupaka, Sachin Parate, Amit Bhanushali, Latha Thammareddi, P. Paramasivan.
© 2024.
15 pages.
|
M. Lishmah Dominic, P. S. Venkateswaran, Latha Thamma Reddi, Sandeep Rangineni, R. Regin, S. Suman Rajest.
© 2024.
15 pages.
|
S. Sivabala, P. Vidyasri.
© 2024.
23 pages.
|
H. Hajra, G. Jayalakshmi.
© 2024.
22 pages.
|
Anusha Thakur.
© 2024.
15 pages.
|
|
|