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Statistics for data scientists = an ...
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Kaptein, Maurits.
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Statistics for data scientists = an introduction to probability, statistics, and data analysis /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Statistics for data scientists/ by Maurits Kaptein, Edwin van den Heuvel.
Reminder of title:
an introduction to probability, statistics, and data analysis /
Author:
Kaptein, Maurits.
other author:
Heuvel, Edwin van den.
Published:
Cham :Springer International Publishing : : 2022.,
Description:
xxiv, 321 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:
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.
Contained By:
Springer Nature eBook
Subject:
Mathematical analysis - Statistical methods. -
Online resource:
https://doi.org/10.1007/978-3-030-10531-0
ISBN:
9783030105310
Statistics for data scientists = an introduction to probability, statistics, and data analysis /
Kaptein, Maurits.
Statistics for data scientists
an introduction to probability, statistics, and data analysis /[electronic resource] :by Maurits Kaptein, Edwin van den Heuvel. - Cham :Springer International Publishing :2022. - xxiv, 321 p. :ill. (some col.), digital ;24 cm. - Undergraduate topics in computer science,2197-1781. - Undergraduate topics in computer science..
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.
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.
ISBN: 9783030105310
Standard No.: 10.1007/978-3-030-10531-0doiSubjects--Topical Terms:
3592081
Mathematical analysis
--Statistical methods.
LC Class. No.: QA276.4 / .K36 2022
Dewey Class. No.: 519.50285
Statistics for data scientists = an introduction to probability, statistics, and data analysis /
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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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Computer Science (SpringerNature-11645)
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W9438861
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11.線上閱覽_V
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EB QA276.4 .K36 2022
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