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Cluster Weighted Beta Regression: A Simulation Study Read chapter Read first chapter

2019 | OriginalPaper | Chapter

Experimental Design Issues in Big Data: The Question of Bias

Authors : Elena Pesce, Eva Riccomagno, Henry P. Wynn

Published in: Statistical Learning of Complex Data

Publisher: Springer International Publishing

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Abstract

Data can be collected in scientific studies via a controlled experiment or passive observation. Big data is often collected in a passive way, e.g. from social media. In studies of causation great efforts are made to guard against bias and hidden confounders or feedback which can destroy the identification of causation by corrupting or omitting counterfactuals (controls). Various solutions of these problems are discussed, including randomisation.

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previous chapter Big Data and Network Analysis: A Combined Approach to Model Online News
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Metadata
Title
Experimental Design Issues in Big Data: The Question of Bias
Authors
Elena Pesce
Eva Riccomagno
Henry P. Wynn
Copyright Year
2019
Book
Statistical Learning of Complex Data

Print ISBN: 978-3-030-21139-4

Electronic ISBN: 978-3-030-21140-0

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-21140-0_20

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