Idioma: Inglés
Publicado por National Academies Press, 2016
ISBN 10: 0309392020 ISBN 13: 9780309392020
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Idioma: Inglés
Publicado por National Academies Press, 2016
ISBN 10: 0309392020 ISBN 13: 9780309392020
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
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Idioma: Inglés
Publicado por National Academies Press, Washington, 2016
ISBN 10: 0309392020 ISBN 13: 9780309392020
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Añadir al carritoPaperback. Condición: new. Paperback. Questions about the reproducibility of scientific research have been raised in numerous settings and have gained visibility through several high-profile journal and popular press articles. Quantitative issues contributing to reproducibility challenges have been considered (including improper data measurement and analysis, inadequate statistical expertise, and incomplete data, among others), but there is no clear consensus on how best to approach or to minimize these problems. A lack of reproducibility of scientific results has created some distrust in scientific findings among the general public, scientists, funding agencies, and industries. While studies fail for a variety of reasons, many factors contribute to the lack of perfect reproducibility, including insufficient training in experimental design, misaligned incentives for publication and the implications for university tenure, intentional manipulation, poor data management and analysis, and inadequate instances of statistical inference.The workshop summarized in this report was designed not to address the social and experimental challenges but instead to focus on the latter issues of improper data management and analysis, inadequate statistical expertise, incomplete data, and difficulties applying sound statistic inference to the available data. Many efforts have emerged over recent years to draw attention to and improve reproducibility of scientific work. This report uniquely focuses on the statistical perspective of three issues: the extent of reproducibility, the causes of reproducibility failures, and the potential remedies for these failures. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Idioma: Inglés
Publicado por National Academies Press, 2016
ISBN 10: 0309392020 ISBN 13: 9780309392020
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Idioma: Inglés
Publicado por National Academies Press, 2016
ISBN 10: 0309392020 ISBN 13: 9780309392020
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EUR 50,25
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Idioma: Inglés
Publicado por National Academies Press, 2016
ISBN 10: 0309392020 ISBN 13: 9780309392020
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Añadir al carritoPaperback. Condición: Brand New. 119 pages. 9.75x7.00x0.50 inches. In Stock.
Idioma: Inglés
Publicado por National Academies Press, 2016
ISBN 10: 0309392020 ISBN 13: 9780309392020
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Añadir al carritoCondición: New. 2016. Illustrated. paperback. . . . . . Books ship from the US and Ireland.
Idioma: Inglés
Publicado por National Academies Press, 2016
ISBN 10: 0309392020 ISBN 13: 9780309392020
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Idioma: Inglés
Publicado por National Academies Press, 2016
ISBN 10: 0309392020 ISBN 13: 9780309392020
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Idioma: Inglés
Publicado por National Academies Press, Washington, 2016
ISBN 10: 0309392020 ISBN 13: 9780309392020
Librería: AussieBookSeller, Truganina, VIC, Australia
EUR 84,62
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Añadir al carritoPaperback. Condición: new. Paperback. Questions about the reproducibility of scientific research have been raised in numerous settings and have gained visibility through several high-profile journal and popular press articles. Quantitative issues contributing to reproducibility challenges have been considered (including improper data measurement and analysis, inadequate statistical expertise, and incomplete data, among others), but there is no clear consensus on how best to approach or to minimize these problems. A lack of reproducibility of scientific results has created some distrust in scientific findings among the general public, scientists, funding agencies, and industries. While studies fail for a variety of reasons, many factors contribute to the lack of perfect reproducibility, including insufficient training in experimental design, misaligned incentives for publication and the implications for university tenure, intentional manipulation, poor data management and analysis, and inadequate instances of statistical inference.The workshop summarized in this report was designed not to address the social and experimental challenges but instead to focus on the latter issues of improper data management and analysis, inadequate statistical expertise, incomplete data, and difficulties applying sound statistic inference to the available data. Many efforts have emerged over recent years to draw attention to and improve reproducibility of scientific work. This report uniquely focuses on the statistical perspective of three issues: the extent of reproducibility, the causes of reproducibility failures, and the potential remedies for these failures. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.