Statistical Foundations, Reasoning and Inference - For Science and Data Science (Paperback, 1st ed. 2021)

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.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Springer Series in Statistics
Release date:	October 2022
First published:	2021
Authors:	Goeran Kauermann • Helmut Kuchenhoff • Christian Heumann
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	356
Edition:	1st ed. 2021
ISBN-13:	978-3-03-069829-4
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics Books > Computing & IT > General theory of computing > Data structures Books > Computing & IT > Computer programming > Algorithms & procedures Books > Computing & IT > Applications of computing > Databases > Data mining Books > Computing & IT > Applications of computing > Artificial intelligence > General Promotions
LSN:	3-03-069829-7
Barcode:	9783030698294

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