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RT Book, Whole SR Electronic DC OPAC T1 Statistics for Data Scientists : An Introduction to Probability, Statistics, and Data Analysis / by Maurits Kaptein, Edwin van den Heuvel T2 Undergraduate Topics in Computer Science. ISSN:21971781 A1 Kaptein, Maurits A1 van den Heuvel, Edwin A1 SpringerLink (Online service) YR 2022 FD 2022 SP XXIV, 321 p. 53 illus., 19 illus. in color K1 Computer science -- Mathematics K1 Mathematical statistics K1 Statistics K1 Probabilities K1 Probability and Statistics in Computer Science K1 Statistical Theory and Methods K1 Probability Theory ED 1st ed. 2022. PB Springer International Publishing : Imprint: Springer PP Cham SN 9783030105310 LA English (英語) CL LCC:QA76.9.M35 CL LCC:QA276-280 CL DC23:004.0151 NO 1 A First Look at Data -- 2 Sampling Plans and Estimates -- 3 Probability Theory -- 4 Random Variables and Distributions -- 5 Estimation -- 6 Multiple Random Variables -- 7 Making Decisions in Uncertainty -- 8 Bayesian Statistics NO This book provides an undergraduate introduction to analysing data for data science, computer science, and quantitative social science students. It uniquely combines a hands-on approach to data analysis – supported by numerous real data examples and reusable [R] code – with a rigorous treatment of probability and statistical principles. Where contemporary undergraduate textbooks in probability theory or statistics often miss applications and an introductory treatment of modern methods (bootstrapping, Bayes, etc.), and where applied data analysis books often miss a rigorous theoretical treatment, this book provides an accessible but thorough introduction into data analysis, using statistical methods combining the two viewpoints. The book further focuses on methods for dealing with large data-sets and streaming-data and hence provides a single-course introduction of statistical methods for data science NO HTTP:URL=https://doi.org/10.1007/978-3-030-10531-0 NO 書誌ID=EB00003725; LK [E Book]https://doi.org/10.1007/978-3-030-10531-0 OL 30