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220303 ||| eng |
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|a 9783030105310
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| 100 |
1 |
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|a Kaptein, Maurits
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| 245 |
0 |
0 |
|a Statistics for Data Scientists
|h Elektronische Ressource
|b An Introduction to Probability, Statistics, and Data Analysis
|c by Maurits Kaptein, Edwin van den Heuvel
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| 250 |
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|a 1st ed. 2022
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| 260 |
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|a Cham
|b Springer International Publishing
|c 2022, 2022
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| 300 |
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|a XXIV, 321 p. 53 illus., 19 illus. in color
|b online resource
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| 505 |
0 |
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|a 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
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| 653 |
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|a Mathematical statistics
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| 653 |
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|a Statistical Theory and Methods
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| 653 |
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|a Computer science / Mathematics
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| 653 |
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|a Probability and Statistics in Computer Science
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| 653 |
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|a Statistics
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| 653 |
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|a Probability Theory
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| 653 |
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|a Probabilities
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| 700 |
1 |
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|a van den Heuvel, Edwin
|e [author]
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
|
| 490 |
0 |
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|a Undergraduate Topics in Computer Science
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| 028 |
5 |
0 |
|a 10.1007/978-3-030-10531-0
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| 856 |
4 |
0 |
|u https://doi.org/10.1007/978-3-030-10531-0?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 004.0151
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| 520 |
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|a 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
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