Please use this identifier to cite or link to this item: https://openlibrary-repo.ecampusontario.ca/jspui/handle/123456789/824
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dc.contributor.authorLilja, David R.-
dc.creatorLilja, David R.-
dc.date.accessioned2020-09-01T20:30:26Z-
dc.date.available2020-09-01T20:30:26Z-
dc.date.issued2016-
dc.identifier5eed5def-f93b-4bc6-b205-637f3bae4103-
dc.identifier.citationLilja, David J. (2016). Linear Regression Using R: An Introduction to Data Modeling. University of Minnesota Libraries Publishing. Retrieved from the University of Minnesota Digital Conservancy, http://hdl.handle.net/11299/189222.-
dc.identifier.isbn9781946135001-
dc.identifier.urihttps://openlibrary-repo.ecampusontario.ca/jspui/handle/123456789/824-
dc.description.tableofcontents1. Introduction-
dc.description.tableofcontents2. Understand Your Data-
dc.description.tableofcontents3. One-Factor Regression-
dc.description.tableofcontents4. Multi-factor Regression-
dc.description.tableofcontents5. Predicting Responses-
dc.description.tableofcontents6. Reading Data into the R Environment-
dc.language.isoengen_US
dc.publisherUniversity of Minnesota Libraries Publishing-
dc.rightsCC BY-NC | https://creativecommons.org/licenses/by-nc/4.0/en_US
dc.titleLinear Regression Using R : An Introduction to Data Modelingen_US
dc.typeBook-
dc.typeOther-
dcterms.accessRightsOpen Access-
dcterms.educationLevelAdult and Continuing Education-
dc.identifier.slughttps://openlibrary.ecampusontario.ca/catalogue/item/?id=5eed5def-f93b-4bc6-b205-637f3bae4103-
ecO-OER.AdoptedNo-
ecO-OER.AncillaryMaterialYes-
ecO-OER.InstitutionalAffiliationUniversity of Minnesotaen_US
ecO-OER.ISNI0000 0004 1936 8657-
ecO-OER.ReviewedNo-
dc.identifier.doihttps://doi.org/10.24926/8668/1301-
ecO-OER.AccessibilityStatementUnknown-
lrmi.learningResourceTypeLearning Resource - Textbook-
lrmi.learningResourceTypeLearning Resource - Data/Dataset-
ecO-OER.POD.compatibleYes-
dc.description.abstractLinear Regression Using R: An Introduction to Data Modeling 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.en_US
dc.subject.otherTechnology - Programming & Programs-
dc.subject.otherTechnology - Research & Data-
ecO-OER.ItemTypeTextbook-
ecO-OER.MediaFormatPDF-
Appears in Collections:Ontario OER Collection

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LinearRegression_fulltext.pdf.jpg%%cover%%37.5 kBJPEGView/Open
LinearRegression_fulltext.pdf%%downloads%% Digital PDF1.71 MBPDFView/Open
all-data.csv%%ancillary%% Student Resources: All Data (.csv file)287.98 kBUnknownView/Open
read-data-v4.R%%ancillary%% Student Resources: Read Data (.r file)2.9 kBUnknownView/Open


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