43,59 €
Linear Regression
Linear Regression
43,59 €
  • Išsiųsime per 14–18 d.d.
Linear regression is the workhorse of data analysis. It is the first step, and often the only step, in fitting a simple model to data. This brief book explains the essential mathematics required to understand and apply regression analysis. The tutorial style of writing, accompanied by over 30 diagrams, offers a visually intuitive account of linear regression, including a brief overview of nonlinear and Bayesian regression. Hands-on experience is provided in the form of numerical examples, imple…
43.59
SKAITYTAKNYGA
  • Autorius: James V Stone
  • Leidėjas:
  • Metai: 20220128
  • Puslapiai: 128
  • ISBN-10: 1916279198
  • ISBN-13: 9781916279193
  • Formatas: 15.2 x 22.9 x 0.7 cm, minkšti viršeliai
  • Kalba: Anglų

Linear Regression + nemokamas atvežimas! | James V Stone | knygos.lt

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Linear regression is the workhorse of data analysis. It is the first step, and often the only step, in fitting a simple model to data. This brief book explains the essential mathematics required to understand and apply regression analysis. The tutorial style of writing, accompanied by over 30 diagrams, offers a visually intuitive account of linear regression, including a brief overview of nonlinear and Bayesian regression. Hands-on experience is provided in the form of numerical examples, implemented online with Python and Matlab code. Supported by a comprehensive glossary and tutorial appendices, this book is an ideal introduction to regression analysis.
43,59 €
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43,59 € Nauja knyga
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Linear regression is the workhorse of data analysis. It is the first step, and often the only step, in fitting a simple model to data. This brief book explains the essential mathematics required to understand and apply regression analysis. The tutorial style of writing, accompanied by over 30 diagrams, offers a visually intuitive account of linear regression, including a brief overview of nonlinear and Bayesian regression. Hands-on experience is provided in the form of numerical examples, implemented online with Python and Matlab code. Supported by a comprehensive glossary and tutorial appendices, this book is an ideal introduction to regression analysis.

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