Statistics is Easy: Case Studies on Real Scientific Datasets
Computational analysis of natural science experiments often confronts noisy data due to natural variability in environment or measurement. Drawing conclusions in the face of such noise entails a statistical analysis.Parametric statistical methods assume that the data is a sample from a population that can be characterized by a specific distribution (e.g., a normal distribution). When the assumption is true, parametric approaches can lead to high confidence predictions. However, in many cases particular distribution assumptions do not hold. In that case, assuming a distribution may yield false conclusions.The companion book Statistics is Easy!…
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Produktdetails
Weitere Autoren: Tyagi, Sudarshini / Shasha, Dennis
- ISBN: 978-1-63639-091-8
- EAN: 9781636390918
- Produktnummer: 36441698
- Verlag: Morgan & Claypool
- Sprache: Englisch
- Erscheinungsjahr: 2021
- Seitenangabe: 74 S.
- Masse: H24.1 cm x B19.6 cm x D0.8 cm 356 g
- Gewicht: 356
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