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Da: GreatBookPrices, Columbia, MD, U.S.A.
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Lingua: Inglese
Editore: Elsevier Science Publishing Co Inc, 2016
ISBN 10: 0128047534 ISBN 13: 9780128047538
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
EUR 66,39
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Da: Ria Christie Collections, Uxbridge, Regno Unito
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Da: Chiron Media, Wallingford, Regno Unito
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
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Aggiungi al carrelloCondizione: New. An introductory guide to statistics aimed specifically at the neuroscience audience Contains numerous examples with actual data that is used in the analysis Gives the investigators a starting pointing for evaluating data in easy-t.
Da: preigu, Osnabrück, Germania
EUR 132,90
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Fundamental Statistical Principles for the Neurobiologist | A Survival Guide | Stephen W. Scheff | Taschenbuch | Einband - fest (Hardcover) | Englisch | 2016 | Elsevier Inc | EAN 9780128047538 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
Da: Brook Bookstore On Demand, Napoli, NA, Italia
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Da: Revaluation Books, Exeter, Regno Unito
EUR 58,37
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Aggiungi al carrelloPaperback. Condizione: Brand New. 1st edition. 234 pages. 8.75x6.00x0.50 inches. In Stock. This item is printed on demand.
Lingua: Inglese
Editore: Elsevier Science Publishing Co Inc, 2016
ISBN 10: 0128047534 ISBN 13: 9780128047538
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
EUR 87,79
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 150,00
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Fundamental Statistical Principles for Neurobiologists introduces readers to basic experimental design and statistical thinking in a comprehensive, relevant manner. This book is an introductory statistics book that covers fundamental principles written by a neuroscientist who understands the plight of the neuroscience graduate student and the senior investigator. It summarizes the fundamental concepts associated with statistical analysis that are useful for the neuroscientist, and provides understanding of a particular test in language that is more understandable to this specific audience, with the overall purpose of explaining which statistical technique should be used in which situation. Different types of data are discussed such as how to formulate a research hypothesis, the primary types of statistical errors and statistical power, followed by how to actually graph data and what kinds of mistakes to avoid. Chapters discuss variance, standard deviation, standard error, mean, confidence intervals, correlation, regression, parametric vs. nonparametric statistical tests, ANOVA, and post hoc analyses. Finally, there is a discussion on how to deal with data points that appear to be 'outliers' and what to do when there is missing data, an issue that has not sufficiently been covered in literature. Englisch.
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 113,34
Quantità: 2 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Fundamental Statistical Principles for Neurobiologists introduces readers to basic experimental design and statistical thinking in a comprehensive, relevant manner. This book is an introductory statistics book that covers fundamental principles written by a neuroscientist who understands the plight of the neuroscience graduate student and the senior investigator. It summarizes the fundamental concepts associated with statistical analysis that are useful for the neuroscientist, and provides understanding of a particular test in language that is more understandable to this specific audience, with the overall purpose of explaining which statistical technique should be used in which situation. Different types of data are discussed such as how to formulate a research hypothesis, the primary types of statistical errors and statistical power, followed by how to actually graph data and what kinds of mistakes to avoid. Chapters discuss variance, standard deviation, standard error, mean, confidence intervals, correlation, regression, parametric vs. nonparametric statistical tests, ANOVA, and post hoc analyses. Finally, there is a discussion on how to deal with data points that appear to be 'outliers' and what to do when there is missing data, an issue that has not sufficiently been covered in literature.