Between Dec 19, 2024 and Jan 2, 2025, datasets can be submitted to DRUM but will not be processed until after the break. Staff will not be available to answer email during this period, and will not be able to provide DOIs until after Jan 2. If you are in need of a DOI during this period, consider Dryad or OpenICPSR. Submission responses to the UDC may also be delayed during this time.
 

Linear Regression Using R: An Introduction to Data Modeling, 2nd Edition

Lilja, David J
Linse, Greta M
2022
Thumbnail Image

View/Download File

Full text, 2nd edition (3.06 MB)
 All data csv file (287.98 KB)
 Read data R file (2.9 KB)

Persistent link to this item

https://hdl.handle.net/11299/189222
Statistics
View Statistics

Journal Title

Journal ISSN

Volume Title

Title

Linear Regression Using R: An Introduction to Data Modeling, 2nd Edition

Authors

Published Date

2022

Publisher

University of Minnesota Libraries Publishing

Type

Book

Abstract

Linear Regression Using R: An Introduction to Data Modeling, 2nd Edition presents one of the fundamental data modeling techniques in an informal tutorial style. Learn how to predict system outputs from measured data using a detailed step-by-step process to develop, train, and test reliable regression models. Key modeling and programming concepts are intuitively described using the R programming language. All of the necessary resources are freely available online.

Keywords

Description

Includes full text in PDF, supplemental data in .csv, and supplemental data in .R

Related to

Replaces

The 1st Edition of this work is available here:
http://hdl.handle.net/11299/189222.1

License

Collections

Open Monographs

Series/Report Number

Funding information

Isbn identifier

978-1-946135-83-4

Doi identifier

https://doi.org/10.24926/8668/1301

Previously Published Citation

Other identifiers

Suggested citation

Lilja, David J; Linse, Greta M. (2022). Linear Regression Using R: An Introduction to Data Modeling, 2nd Edition. Retrieved from the University Digital Conservancy, https://doi.org/10.24926/8668/1301.

Content distributed via the University Digital Conservancy may be subject to additional license and use restrictions applied by the depositor. By using these files, users agree to the Terms of Use. Materials in the UDC may contain content that is disturbing and/or harmful. For more information, please see our statement on harmful content in digital repositories.