000			a
999			_c33736 _d33736
008			250225b xxu||||| |||| 00| 0 eng d
020			_a9783030395605
082			_a519.5 _bGIL
100			_aGillard, Jonathan
245			_aA first course in statistical inference
260			_bSpringer, _c2020 _aCham :
300			_ax, 164 p. ; _bill., (some col.), _c24 cm
365			_b39.99 _c€ _d93.20
490			_aSpringer undergraduate mathematics series
504			_aIncludes index.
520			_aThis 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.
650			_aAcceptance region
650			_aCentral Limit Theorem
650			_aChi-squared distribution
650			_aCumulative distribution function
650			_aDiscrete random variable
650			_aNull hypothesis
650			_ap-value
650			_aPoisson distribution
650			_aProbability density function
650			_aProbability mass function
650			_aRandomsample
650			_aSignificance level
650			_aStudent's t-distribution
942			_2ddc _cBK