Statistical Data Analytics (PDF) – Foundations for Data Mining, Informatics, and Knowledge Discovery
A comprehensive introduction to statistical methods for data mining and knowledge discovery
Applications of data mining and ‘big data’ increasingly take center stage in our modern, knowledge-driven society, supported by advances in computing power, automated data acquisition, social media development, and interactive, linkable internet software. This ebook Statistical Data Analytics presents a coherent, technical introduction to modern statistical learning and analytics, starting from the core foundations of statistics and probability. It includes an overview of probability and statistical distributions, data manipulation and visualization basics, and the central components of standard statistical inferences. Most of the text extends beyond these introductory topics to supervised learning in linear regression, generalized linear models, and classification analytics. Finally, the introduction of unsupervised learning via dimension reduction, cluster analysis, and market basket analysis.
Extensive examples using actual data (with sample R programming code) are provided, illustrating diverse informatics sources in genomics, biomedicine, ecological remote sensing, astronomy, socioeconomics, marketing, advertising, and finance, among many others.
Statistical Data Analytics:
This ebook will appeal as a classroom or training textbook to intermediate and advanced undergraduates and beginning graduate students with sufficient calculus and matrix algebra backgrounds. It will also serve as a sourcebook on statistical informatics and data analytics foundations for practitioners who regularly apply statistical learning to their modern data.
978-1118619650, 978-1119043171
NOTE: This sale only includes the ebook Statistical Data Analytics: Foundations for Data Mining, Informatics, and Knowledge Discovery in PDF. No access codes included.
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