Linear Regression Using R An Introduction to Data Modeling
Linear 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...
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| Format: | Electronic eBook |
| Language: | English |
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[Place of publication not identified]
University of Minnesota Libraries Publishing
[2016]
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| Series: | Open textbook library.
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| Subjects: | |
| Online Access: | Access online version |
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| 100 | 1 | |a Lilja, David J. |e author | |
| 245 | 0 | 0 | |a Linear Regression Using R |b An Introduction to Data Modeling |c David Lilja |
| 264 | 2 | |a Minneapolis, MN |b Open Textbook Library | |
| 264 | 1 | |a [Place of publication not identified] |b University of Minnesota Libraries Publishing |c [2016] | |
| 264 | 4 | |c ©2016. | |
| 300 | |a 1 online resource | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 0 | |a Open textbook library. | |
| 505 | 0 | |a 1 Introduction -- 1.1 What is a Linear Regression Model? -- 1.2 What is R? -- 1.3 What's Next? -- 2 Understand Your Data -- 2.1 Missing Values -- 2.2 Sanity Checking and Data Cleaning -- 2.3 The Example Data -- 2.4 Data Frames -- 2.5 Accessing a Data Frame -- 3 One-Factor Regression -- 3.1 Visualize the Data -- 3.2 The Linear Model Function -- 3.3 Evaluating the Quality of the Model -- 3.4 Residual Analysis -- 4 Multi-factor Regression -- 4.1 Visualizing the Relationships in the Data -- 4.2 Identifying Potential Predictors -- 4.3 The Backward Elimination Process -- 4.4 An Example of the Backward Elimination Process -- 4.5 Residual Analysis -- 4.6 When Things Go Wrong -- 5 Predicting Responses -- 5.1 Data Splitting for Training and Testing -- 5.2 Training and Testing -- 5.3 Predicting Across Data Sets -- 6 Reading Data into the R Environment -- 6.1 Reading CSV files -- 7 Summary8 A Few Things to Try NextBibliographyIndex | |
| 520 | 0 | |a Linear 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. | |
| 542 | 1 | |f Attribution-NonCommercial | |
| 546 | |a In English. | ||
| 588 | 0 | |a Description based on online resource | |
| 650 | 0 | |a Mathematics |v Textbooks | |
| 710 | 2 | |a Open Textbook Library |e distributor | |
| 856 | 4 | 0 | |u https://open.umn.edu/opentextbooks/textbooks/399 |z Access online version |