Statistical Foundations, Reasoning and Inference : For Science and Data Science /

This textbook provides a comprehensive introduction to statistical principles, concepts and methods that are essential in modern statistics and data science. The topics covered include likelihood-based inference, Bayesian statistics, regression, statistical tests and the quantification of uncertaint...

Full description

Bibliographic Details
Main Authors: Kauermann, Göran (Author), Küchenhoff, Helmut (Author), Heumann, Christian (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2021.
Edition:1st ed. 2021.
Series:Springer Series in Statistics,
Subjects:
Online Access:Connect to the full text of this electronic book

MARC

Tag First Indicator Second Indicator Subfields
LEADER 00000nam a22000005i 4500
001 in00004375608
006 m o d
007 cr nn 008mamaa
008 210930s2021 sz | o |||| 0|eng d
005 20230330185030.0
020 |a 9783030698270 
024 7 |a 10.1007/978-3-030-69827-0  |2 doi 
035 |a (DE-He213)978-3-030-69827-0 
035 |a in00004375608 
050 4 |a QA276-280 
072 7 |a PBT  |2 bicssc 
072 7 |a MAT029000  |2 bisacsh 
072 7 |a PBT  |2 thema 
082 0 4 |a 519.5  |2 23 
100 1 |a Kauermann, Göran.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
245 1 0 |a Statistical Foundations, Reasoning and Inference :  |b For Science and Data Science /  |c by Göran Kauermann, Helmut Küchenhoff, Christian Heumann. 
250 |a 1st ed. 2021. 
264 1 |a Cham :  |b Springer International Publishing :  |b Imprint: Springer,  |c 2021. 
300 |a 1 online resource (XIII, 356 pages 87 illustrations, 10 illustrations in color.) 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
490 1 |a Springer Series in Statistics,  |x 2197-568X 
505 0 |a Introduction -- Background in Probability -- Parametric Statistical Models -- Maximum Likelihood Inference -- Bayesian Statistics -- Statistical Decisions -- Regression -- Bootstrapping -- Model Selection and Model Averaging -- Multivariate and Extreme Value Distributions -- Missing and Deficient Data -- Experiments and Causality. 
520 |a This textbook provides a comprehensive introduction to statistical principles, concepts and methods that are essential in modern statistics and data science. The topics covered include likelihood-based inference, Bayesian statistics, regression, statistical tests and the quantification of uncertainty. Moreover, the book addresses statistical ideas that are useful in modern data analytics, including bootstrapping, modeling of multivariate distributions, missing data analysis, causality as well as principles of experimental design. The textbook includes sufficient material for a two-semester course and is intended for master's students in data science, statistics and computer science with a rudimentary grasp of probability theory. It will also be useful for data science practitioners who want to strengthen their statistics skills. 
650 0 |a Statistics . 
650 0 |a Data structures (Computer science). 
650 0 |a Artificial intelligence. 
650 0 |a Data mining. 
650 1 4 |a Statistical Theory and Methods.  |0 https://scigraph.springernature.com/ontologies/product-market-codes/S11001 
650 2 4 |a Data Structures and Information Theory.  |0 https://scigraph.springernature.com/ontologies/product-market-codes/I15009 
650 2 4 |a Artificial Intelligence.  |0 https://scigraph.springernature.com/ontologies/product-market-codes/I21000 
650 2 4 |a Data Mining and Knowledge Discovery.  |0 https://scigraph.springernature.com/ontologies/product-market-codes/I18030 
650 2 4 |a Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.  |0 https://scigraph.springernature.com/ontologies/product-market-codes/S17020 
655 7 |a Electronic books.  |2 local 
700 1 |a Küchenhoff, Helmut.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
700 1 |a Heumann, Christian.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer Nature eBook 
776 0 8 |i Printed edition:  |z 9783030698263 
776 0 8 |i Printed edition:  |z 9783030698287 
776 0 8 |i Printed edition:  |z 9783030698294 
830 0 |a Springer Series in Statistics,  |x 2197-568X 
856 4 0 |u http://proxy.library.tamu.edu/login?url=https://doi.org/10.1007/978-3-030-69827-0  |z Connect to the full text of this electronic book  |t 0 
950 |a Mathematics and Statistics (SpringerNature-11649) 
950 |a Mathematics and Statistics (R0) (SpringerNature-43713) 
955 |a Springer EBA Purchase 
999 f f |s 36c6f06e-eaa6-4329-8a49-4fdf741b9f01  |i e247ba5d-0e75-39b7-a491-350ce0ea1202  |t 0 
952 f f |a Texas A&M University  |b College Station  |c Electronic Resources  |d Available Online  |t 0  |e QA276-280   |h Library of Congress classification 
998 f f |a QA276-280   |t 0  |l Available Online