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[null,"1.","Record Nr.",null,"UNINA9910583372603321"]
[null,null,"Autore",null,"Smalheiser Neil R."]
[null,null,"Titolo",null,"Data literacy : how to make your experiments robust and reproducible / / Neil Smalheiser, MD, PhD, Associate Professor in Psychiatry, Department of Psychiatry and Psychiatric Institute, University of Illinois School of Medicine, USA"]
[null,null,"Pubbl/distr/stampa",null,"Amsterdam : , : Academic Press, an imprint of Elsevier, , [2017]"]
[{"$nulls":4},"�2017"]
[null,null,"Descrizione fisica",null,"1 online resource (xvii, 261 pages) : illustrations (some color)"]
[null,null,"Collana",null,"Gale eBooks"]
[null,null,"Disciplina",null,"006.312"]
[null,null,"Soggetti",null,"Data mining"]
[{"$nulls":4},"Research - Data processing"]
[{"$nulls":4},"Medicine - Research - Data processing"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references at the end of each chapters and index."]
[null,null,"Nota di contenuto",null,"A. Designing your experiment -- B. Getting a \"feel\" for your data -- C. Statistics (without much math!) -- D. Make your data go farther."]
[null,null,null,"Sommario/riassunto","This book provides an overview of the basic concepts and skills involved in handling scientific data, and examines the processes that are necessary when carrying out a scientific study and some of the factors that make a study robust and reproducible. Experimental design, data cleansing and preparation, statistical analysis, data management, and reporting are among the topics discussed."]