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| LEADER |
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| 008 |
210930s2021 sz | o |||| 0|eng d |
| 005 |
20230330185030.0 |
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|a 9783030698270
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| 024 |
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|
|a 10.1007/978-3-030-69827-0
|2 doi
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|a (DE-He213)978-3-030-69827-0
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| 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 |
|
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|a text
|b txt
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| 337 |
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|a computer
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|2 rdamedia
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| 338 |
|
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|a online resource
|b cr
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| 347 |
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|a text file
|b PDF
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| 490 |
1 |
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|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 |
|
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|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.
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|
| 700 |
1 |
|
|a Heumann, Christian.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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| 710 |
2 |
|
|a SpringerLink (Online service)
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|t Springer Nature eBook
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| 776 |
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8 |
|i Printed edition:
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| 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 |
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|
| 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 |
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f |
|a QA276-280
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