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Statistical Data Cleaning with Applications in R (Hardcover)
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Statistical Data Cleaning with Applications in R (Hardcover)
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A comprehensive guide to automated statistical data cleaning The
production of clean data is a complex and time-consuming process
that requires both technical know-how and statistical expertise.
Statistical Data Cleaning brings together a wide range of
techniques for cleaning textual, numeric or categorical data. This
book examines technical data cleaning methods relating to data
representation and data structure. A prominent role is given to
statistical data validation, data cleaning based on predefined
restrictions, and data cleaning strategy. Key features: Focuses on
the automation of data cleaning methods, including both theory and
applications written in R. Enables the reader to design data
cleaning processes for either one-off analytical purposes or for
setting up production systems that clean data on a regular basis.
Explores statistical techniques for solving issues such as
incompleteness, contradictions and outliers, integration of data
cleaning components and quality monitoring. Supported by an
accompanying website featuring data and R code. This book enables
data scientists and statistical analysts working with data to
deepen their understanding of data cleaning as well as to upgrade
their practical data cleaning skills. It can also be used as
material for a course in data cleaning and analyses.
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