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|a 9783030457990
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| 100 |
1 |
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|a Stapor, Katarzyna
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| 245 |
0 |
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|a Introduction to Probabilistic and Statistical Methods with Examples in R
|h Elektronische Ressource
|c by Katarzyna Stapor
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| 250 |
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|a 1st ed. 2020
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| 260 |
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|a Cham
|b Springer International Publishing
|c 2020, 2020
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| 300 |
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|a VIII, 157 p. 33 illus., 24 illus. in color
|b online resource
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| 505 |
0 |
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|a Elements of Probability Theory -- Descriptive and Inferential Statistics -- Linear Regression and Correlation
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| 653 |
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|a Data Engineering
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| 653 |
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|a Engineering mathematics
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| 653 |
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|a Statistics
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| 653 |
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|a Applied Statistics
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| 653 |
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|a Engineering Mathematics
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| 653 |
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|a Engineering—Data processing
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 490 |
0 |
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|a Intelligent Systems Reference Library
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| 856 |
4 |
0 |
|u https://doi.org/10.1007/978-3-030-45799-0?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 519.5
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| 520 |
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|a This book strikes a healthy balance between theory and applications, ensuring that it doesn’t offer a set of tools with no mathematical roots. It is intended as a comprehensive and largely self-contained introduction to probability and statistics for university students from various faculties, with accompanying implementations of some rudimentary statistical techniques in the language R. The content is divided into three basic parts: the first includes elements of probability theory, the second introduces readers to the basics of descriptive and inferential statistics (estimation, hypothesis testing), and the third presents the elements of correlation and linear regression analysis. Thanks to examples showing how to approach real-world problems using statistics, readers will acquire stronger analytical thinking skills, which are essential for analysts and data scientists alike.
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