Articles liés à Guide to Multiple Regression
Synopsis
This book is intended to equip the reader with concept knowledge, on multilinear regression methods, and develop technical skills, while solving problems with the R programming language. The goal is not to become an expert in both directions. It is rather an incentive to do research on advanced models in data analysis once confidence is gained with the practice of some methods.
Basics in inferential statistics and basics in a programming language are necessary prerequisites to engage well with the content. We believe that using a computer is the only practical means of performing a linear or multilinear regression on a data set of even moderate size. Therefore, our purpose is to make these connections between theory, technology, and applications, as clear as possible.
Features
- Focused summaries of the main statistical methods, followed with solved questions.
- Integration of R as a calculator, and as a programming language in solving each question with ease and accuracy.
- Use of simple coding that illustrates the connection to the theory.
- Suggest progressively alternative codes.
- Visualization and interpretation of the R outputs.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l'auteur
Samia Challal is an associate professor at Glendon College; the bilingual campus of York University. She teaches courses in Analysis, Algebra, and Statistics. Her research draws on partial differential equations applied to fluid dynamics, optimization, homogenization problems, and mathematics education. She received her PhD from the University of Metz, France.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Guide to Multiple Regression
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Chapman and Hall/CRC, 2025
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Hardcover. Etat : new. Hardcover. This book is intended to equip the reader with concept knowledge on multilinear regression methods, and develop technical skills while solving problems with the R programming language. The goal is not to become an expert in both directions. It is rather an incentive to do research on advanced models in data analysis once confidence is gained with the practice of some methods.Basics in inferential statistics and basics in a programming language are necessary prerequisites to engage well with the content. We believe that using a computer is the only practical means of performing a linear or multilinear regression on a data set of even moderate size. Therefore, our purpose is to make these connections between theory, technology, and applications, as clear as possible.FeaturesFocused summaries of the main statistical methods, followed by solved questionsIntegration of R as a calculator, and as a programming language in solving each question with ease and accuracyUse of simple coding that illustrates the connection to the theorySuggest progressively alternative codesVisualization and interpretation of the R outputs This book is intended to equip the reader with concept knowledge, on multilinear regression methods, and develop technical skills, while solving problems with the R programming language. It is rather an incentive to do research on advanced models in data analysis once confidence is gained with the practice of some methods. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9781041018919
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Hardcover. Etat : new. Hardcover. This book is intended to equip the reader with concept knowledge on multilinear regression methods, and develop technical skills while solving problems with the R programming language. The goal is not to become an expert in both directions. It is rather an incentive to do research on advanced models in data analysis once confidence is gained with the practice of some methods.Basics in inferential statistics and basics in a programming language are necessary prerequisites to engage well with the content. We believe that using a computer is the only practical means of performing a linear or multilinear regression on a data set of even moderate size. Therefore, our purpose is to make these connections between theory, technology, and applications, as clear as possible.FeaturesFocused summaries of the main statistical methods, followed by solved questionsIntegration of R as a calculator, and as a programming language in solving each question with ease and accuracyUse of simple coding that illustrates the connection to the theorySuggest progressively alternative codesVisualization and interpretation of the R outputs This book is intended to equip the reader with concept knowledge, on multilinear regression methods, and develop technical skills, while solving problems with the R programming language. It is rather an incentive to do research on advanced models in data analysis once confidence is gained with the practice of some methods. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9781041018919
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Guide to Multiple Regression
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Chapman and Hall/CRC, 2025
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ISBN 13 : 9781041018919
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