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020 _a9783031024337
_9978-3-031-02433-7
024 7 _a10.1007/978-3-031-02433-7
_2doi
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072 7 _aMAT000000
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082 0 4 _a510
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100 1 _aKatari, Manpreet Singh.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_983402
245 1 0 _aStatistics is Easy
_h[electronic resource] :
_bCase Studies on Real Scientific Datasets /
_cby Manpreet Singh Katari, Sudarshini Tyagi, Dennis Shasha.
250 _a1st ed. 2021.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2021.
300 _aXI, 62 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSynthesis Lectures on Mathematics & Statistics,
_x1938-1751
505 0 _aAcknowledgments -- Introduction -- Chick Weight and Diet -- Breast Cancer Classification -- RNA-seq Data Set/ Summary and Perspectives -- Bibliography -- Authors' Biographies.
520 _aComputational 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, gave a (nearly) equation-free introduction to nonparametric (i.e., no distribution assumption) statistical methods. The present book applies data preparation, machine learning, and nonparametric statistics to three quite different life science datasets. We provide the code as applied to each dataset in both R and Python 3. We also include exercises for self-study or classroom use.
650 0 _aMathematics.
_911584
650 0 _aStatistics .
_931616
650 0 _aEngineering mathematics.
_93254
650 1 4 _aMathematics.
_911584
650 2 4 _aStatistics.
_914134
650 2 4 _aEngineering Mathematics.
_93254
700 1 _aTyagi, Sudarshini.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_983406
700 1 _aShasha, Dennis.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_983407
710 2 _aSpringerLink (Online service)
_983408
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031002793
776 0 8 _iPrinted edition:
_z9783031013058
776 0 8 _iPrinted edition:
_z9783031035616
830 0 _aSynthesis Lectures on Mathematics & Statistics,
_x1938-1751
_983409
856 4 0 _uhttps://doi.org/10.1007/978-3-031-02433-7
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