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＜電子ブック＞
A First Course in Statistical Inference / by Jonathan Gillard
(Springer Undergraduate Mathematics Series. ISSN:21974144)

版	1st ed. 2020.
出版者	(Cham : Springer International Publishing : Imprint: Springer)
出版年	2020
大きさ	X, 164 p. 24 illus., 7 illus. in color : online resource
著者標目	*Gillard, Jonathan author SpringerLink (Online service)
件　名	LCSH:Statistics  LCSH:Mathematical statistics—Data processing FREE:Statistical Theory and Methods FREE:Statistics and Computing
一般注記	1 Recap of Probability Fundamentals -- 2 Sampling and Sampling Distributions -- 3 Towards Estimation -- 4 Confidence Intervals -- 5 Hypothesis Testing -- 6 One-way Analysis of Variance (ANOVA) -- 7 Regression: Fitting a Straight Line -- A brief introduction to R -- Solutions to Exercises -- Statistical Tables -- Index This book offers a modern and accessible introduction to Statistical Inference, the science of inferring key information from data. Aimed at beginning undergraduate students in mathematics, it presents the concepts underpinning frequentist statistical theory. Written in a conversational and informal style, this concise text concentrates on ideas and concepts, with key theorems stated and proved. Detailed worked examples are included and each chapter ends with a set of exercises, with full solutions given at the back of the book. Examples using R are provided throughout the book, with a brief guide to the software included. Topics covered in the book include: sampling distributions, properties of estimators, confidence intervals, hypothesis testing, ANOVA, and fitting a straight line to paired data. Based on the author’s extensive teaching experience, the material of the book has been honed by student feedback for over a decade. Assuming only some familiarity with elementary probability, this textbook has been devised for a one semester first course in statistics HTTP:URL=https://doi.org/10.1007/978-3-030-39561-2

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