Big Data Representative of statistical analysis and programming language for graphics! Open source RIn this book, the big data age, the importance of data analysis has come to the fore, nowadays, it covers the scientific analysis methods that can be applied to the statistic in the form desired by the open source free programming language R without using the expensive statistical package. It is a translation of "Mastering Scientific Computing with R" by Packt publishing. It is used for statistical analysis of the differences between groups and the significance of models from basic R concept. This book is armed with an unfamiliar level of statistical terminology, so you need to be prepared to get ready and get ready. Of course, readers who do not have any programming experience with R can also be introduced, and by the time this book is covered, you will become accustomed to combining statistical terms with R. In this book, data management in R, hypothesis testing using parametric and nonparametric models, statistical modeling using linear methods, data nonlinear relationship modeling with kernel regression, matrix operations to improve coding product quality, You can study the use of observational data for modeling, analysis of missing data using multiple substitution methods, multidimensional data reduction using principal component analysis (PCA) singular value decomposition (SVD) factor analysis (FA) All color charts and sources in this book are available for download at www.cyber.co.kr.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
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