<OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:mets="http://www.loc.gov/METS/" xmlns:mods="http://www.loc.gov/mods/v3" xmlns:vl="http://visuallibrary.net/vl" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-07-03T02:52:12Z</responseDate><request verb="GetRecord" metadataPrefix="mets" identifier="1368315">https://ce.visuallibrary.net/ulbd/oai/</request><GetRecord><record><header><identifier>oai:ce.visuallibrary.net/ulbd:1368315</identifier><datestamp>2025-11-26T16:00:33Z</datestamp><setSpec>ulbdce</setSpec><setSpec>book</setSpec></header><metadata><mets:mets xmlns:xlink="http://www.w3.org/1999/xlink" xsi:schemaLocation="http://www.loc.gov/METS/ http://www.loc.gov/standards/mets/version112/mets.xsd" OBJID="7">
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This textbook provides a new tool for the statistical toolkit: data simulations. It shows that using simulation and data-generating models is an excellent way to validate statistical reasoning and to augment study design and statistical analysis with planning and visualization. Although data simulations are not new to professional statisticians, Statistics by Simulation makes the approach accessible to a broader audience, with examples from many fields. It introduces the reasoning behind data simulation and then shows how to apply it in planning experiments or observational studies, developing analytical workflows, deploying model diagnostics, and developing new indices and statistical methods. 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