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010   $a3-319-28316-2
024 7 $a10.1007/978-3-319-28316-6
035   $a(CKB)3710000000765122
035   $a(DE-He213)978-3-319-28316-6
035   $a(MiAaPQ)EBC5587236
035   $a(Au-PeEL)EBL5587236
035   $a(OCoLC)954195049
035   $a(PPN)194515524
035   $a(EXLCZ)993710000000765122
100   $a20160720d2016      u|         0
101 0 $aeng
135   $aurnn|008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 13$aAn Introduction to Statistics with Python $eWith Applications in the Life Sciences /$fby Thomas Haslwanter
205   $a1st ed. 2016.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2016.
215   $a1 online resource (XVII, 278 p. 113 illus., 85 illus. in color.) 
225 1 $aStatistics and Computing,$x1431-8784
311   $a3-319-28315-4 
327   $aPart I: Python and Statistics -- Why Statistics? -- Python -- Data Input -- Display of Statistical Data -- Part II: Distributions and Hypothesis Tests -- Background -- Distributions of One Variable -- Hypothesis Tests -- Tests of Means of Numerical Data -- Tests on Categorical Data -- Analysis of Survival Times -- Part III: Statistical Modelling -- Linear Regression Models -- Multivariate Data Analysis -- Tests on Discrete Data -- Bayesian Statistics -- Solutions -- Glossary -- Index.
330   $aThis textbook provides an introduction to the free software Python and its use for statistical data analysis. It covers common statistical tests for continuous, discrete and categorical data, as well as linear regression analysis and topics from survival analysis and Bayesian statistics. Working code and data for Python solutions for each test, together with easy-to-follow Python examples, can be reproduced by the reader and reinforce their immediate understanding of the topic. With recent advances in the Python ecosystem, Python has become a popular language for scientific computing, offering a powerful environment for statistical data analysis and an interesting alternative to R. The book is intended for master and PhD students, mainly from the life and medical sciences, with a basic knowledge of statistics. As it also provides some statistics background, the book can be used by anyone who wants to perform a statistical data analysis. .
410  0$aStatistics and Computing,$x1431-8784
606   $aStatistics 
606   $aBiostatistics
606   $aComputer mathematics
606   $aProgramming languages (Electronic computers)
606   $aStatistics and Computing/Statistics Programs$3https://scigraph.springernature.com/ontologies/product-market-codes/S12008
606   $aStatistics for Life Sciences, Medicine, Health Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/S17030
606   $aBiostatistics$3https://scigraph.springernature.com/ontologies/product-market-codes/L15020
606   $aComputational Science and Engineering$3https://scigraph.springernature.com/ontologies/product-market-codes/M14026
606   $aProgramming Languages, Compilers, Interpreters$3https://scigraph.springernature.com/ontologies/product-market-codes/I14037
615  0$aStatistics .
615  0$aBiostatistics.
615  0$aComputer mathematics.
615  0$aProgramming languages (Electronic computers).
615 14$aStatistics and Computing/Statistics Programs.
615 24$aStatistics for Life Sciences, Medicine, Health Sciences.
615 24$aBiostatistics.
615 24$aComputational Science and Engineering.
615 24$aProgramming Languages, Compilers, Interpreters.
676   $a519.5
700   $aHaslwanter$b Thomas$4aut$4http://id.loc.gov/vocabulary/relators/aut$0755822
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910254064103321
996   $aAn Introduction to Statistics with Python$92039111
997   $aUNINA