Data Analytics - Foundation
Inference, Regression and Stochastic Processes
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Statistical Science (Statistics) can be described as the science of problem solving in the presence of variability or uncertainty. Data Analytics briefly refers to the techniques used to analyze data to enhance productivity and business gain. Data Analytics practically is the synergy of many building components including mostly tools from Statistics, Probability Theory, powerful algorithmic ideas from Computing, solid fundamentals of Mathematics and, last but not least, specific knowledge of application domains. We can define Data Analytics as the science and the art of making 'good or meaning...
Statistical Science (Statistics) can be described as the science of problem solving in the presence of variability or uncertainty. Data Analytics briefly refers to the techniques used to analyze data to enhance productivity and business gain. Data Analytics practically is the synergy of many building components including mostly tools from Statistics, Probability Theory, powerful algorithmic ideas from Computing, solid fundamentals of Mathematics and, last but not least, specific knowledge of application domains. We can define Data Analytics as the science and the art of making 'good or meaningful' decision based on data sets, within a limited time range, a finite budget and/or computational resource.This book just presents an essential knowledge body for data analytics consisting of statistical inference, linear regression and stochastic analysis. It honestly conveys basic knowledge, theoretical methods and practical approaches to students and professionals, especially ones working in sciences (such as actuarial, computer, environmental, economic, medical), engineering, industry and services. The author hope readers find it joyful to employ the methods in this book.
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