Statistical Data Analytics: Foundations for Data Mining, Informatics and Knowledge Discovery – PDF

Statistical Data Analytics: Foundations for Data Mining, Informatics and Knowledge Discovery – PDF

Statistical Data Analytics (PDF) – Exploring the Foundations for Data Mining, Informatics, and Knowledge Discovery In today’s society, data mining and big data analytics have become increasingly popular. These applications are supported by advances in computing power, automated data acquisition, social media development, and interactive internet software. If you are interested in mastering modern statistical learning and analytics, then the ebook Statistical Data Analytics is the perfect resource for you. It is a technical and comprehensive introduction to statistical methods for data mining and knowledge discovery, starting with the fundamental basics of statistics and probability. The ebook covers an overview of probability and statistical distributions, data manipulation, and visualization, in addition to the central components of standard statistical inferences. It goes beyond these introductory topics to supervised learning in linear regression, generalized linear models, and classification analytics. Furthermore, the book introduces unsupervised learning through dimension reduction, cluster analysis, and market basket analysis. To illustrate the diverse informatics sources in various fields of genomics, biomedicine, ecological remote sensing, astronomy, socioeconomics, marketing, advertising, and finance, the author provides extensive examples using actual data, with sample R programming code included. What Makes Statistical Data Analytics Unique?

• Presents technical details for the highlighted methods, useful for classroom or training textbook to intermediate and advanced undergraduates and beginning graduate students with sufficient calculus and matrix algebra backgrounds.
• Concludes each chapter with a range of exciting and challenging homework exercises using actual data from a variety of informatic application areas.
• Uses the open-source R language as the computational vehicle, along with its growing collection of online packages, to illustrate many of the analyses contained in the ebook.
• Provides a coherent description of the methods while also explaining the extensions to selected intermediate and advanced techniques.

This ebook will be helpful for those interested in statistical informatics and data analytics for practitioners who regularly apply statistical learning to their modern data.

Note: Please be aware that this sale is for the ebook Statistical Data Analytics: Foundations for Data Mining, Informatics, and Knowledge Discovery in PDF format ONLY. This sale does not include access codes.