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020 _a9783031378652
_9978-3-031-37865-2
024 7 _a10.1007/978-3-031-37865-2
_2doi
050 4 _aQA276-280
072 7 _aPBT
_2bicssc
072 7 _aMAT029000
_2bisacsh
072 7 _aPBT
_2thema
100 1 _aSahu, Sujit K.
_eauthor.
_0(orcid)0000-0003-2315-3598
_1https://orcid.org/0000-0003-2315-3598
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_974501
245 1 0 _aIntroduction to Probability, Statistics & R
_h[electronic resource] :
_bFoundations for Data-Based Sciences /
_cby Sujit K. Sahu.
250 _a1st ed. 2024.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2024.
300 _aXIX, 555 p. 109 illus., 82 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aPart I Introduction to basic Statistics and R -- 1 Introduction to basic statistics -- 2 Getting started with R -- Part II Introduction to Probability -- 3 Introduction to probability -- 4 Conditional probability and independence -- 5 Random variables and their probability distributions -- 6 Standard discrete distributions -- 7 Standard continuous distributions -- 8 Joint distributions and the CLT -- Part III Introduction to Statistical Inference -- 9 Introduction to statistical inference -- 10 Methods of point estimation -- 11 Interval estimation -- 12 Hypothesis testing -- Part IV Advanced Distribution Theory and Probability -- 13 Generating functions -- 14 Transformation and transformed distributions -- 15 Multivariate distributions -- 16 Convergence of estimators -- Part V Introduction to statistical modelling -- 17 Simple linear regression model -- 18 Multiple linear regression model -- 19 Analysis of variance -- Appendix: Table of common distributions.
520 _aA strong grasp of elementary statistics and probability, along with basic skills in using R, is essential for various scientific disciplines reliant on data analysis. This book serves as a gateway to learning statistical methods from scratch, assuming a solid background in high school mathematics. Readers gradually progress from basic concepts to advanced statistical modelling, with examples from actuarial, biological, ecological, engineering, environmental, medicine, and social sciences highlighting the real-world relevance of the subject. An accompanying R package enables seamless practice and immediate application, making it ideal for beginners. The book comprises 19 chapters divided into five parts. Part I introduces basic statistics and the R software package, teaching readers to calculate simple statistics and create basic data graphs. Part II delves into probability concepts, including rules and conditional probability, and introduces widely used discrete and continuous probability distributions (e.g., binomial, Poisson, normal, log-normal). It concludes with the central limit theorem and joint distributions for multiple random variables. Part III explores statistical inference, covering point and interval estimation, hypothesis testing, and Bayesian inference. This part is intentionally less technical, making it accessible to readers without an extensive mathematical background. Part IV addresses advanced probability and statistical distribution theory, assuming some familiarity with (or concurrent study of) mathematical methods like advanced calculus and linear algebra. Finally, Part V focuses on advanced statistical modelling using simple and multiple regression and analysis of variance, laying the foundation for further studies in machine learning and data science applicable to various data and decision analytics contexts. Based on years of teaching experience, this textbook includes numerous exercises and makes extensive use of R, making it ideal for year-long data science modules and courses. In addition to university courses, the book amply covers the syllabus for the Actuarial Statistics 1 examination of the Institute and Faculty of Actuaries in London. It also provides a solid foundation for postgraduate studies in statistics and probability, or a reliable reference for statistics.
650 0 _aMathematical statistics.
_967233
650 0 _aStatistics .
_965982
650 0 _aProbabilities.
_965724
650 1 4 _aMathematical Statistics.
_967233
650 2 4 _aStatistics.
_965982
650 2 4 _aProbability Theory.
_967428
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783031378645
776 0 8 _iPrinted edition:
_z9783031378669
856 4 0 _uhttps://doi.org/10.1007/978-3-031-37865-2
912 _aZDB-2-SMA
912 _aZDB-2-SXMS
999 _c58855
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