LEADER 03359nam 22005895 450 001 9911007457403321 005 20250522130306.0 010 $a3-031-86670-3 024 7 $a10.1007/978-3-031-86670-8 035 $a(MiAaPQ)EBC32128681 035 $a(Au-PeEL)EBL32128681 035 $a(CKB)38874965800041 035 $a(DE-He213)978-3-031-86670-8 035 $a(EXLCZ)9938874965800041 100 $a20250522d2025 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aExercise Book of Statistical Inference /$fby Francesca Gasperoni, Francesca Ieva, Anna Maria Paganoni 205 $a1st ed. 2025. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2025. 215 $a1 online resource (346 pages) 225 1 $aLa Matematica per il 3+2,$x2038-5757 ;$v173 311 08$a3-031-86669-X 327 $aPart I: Statistical Inference -- 1 Fundamentals of Probability and Statistics -- 2 Sufficient, Minimal, and Complete Statistics -- 3 Point Estimators -- 4 Uniform Minimum Variance Unbiased Estimators (UMVUEs) -- 5 Likelihood Ratio Test -- 6 Uniformly Most Powerful Test -- 7 Confidence Intervals -- 8 Asymptotic Statistics -- Part II: Regression Models and Analysis of Variance -- 9 Linear Regression -- 10 Generalized Linear Models -- 11 ANOVA: Analysis of Variance -- 12 Summary Exercises -- Appendix A: Probability Distributions. 330 $aThis book was created with the goal of helping students transition from the theoretical and methodological concepts of statistical inference to their implementation on a computer. The first part of the book is primarily focused on exercises to be solved with pen and paper, so that students can apply knowledge derived from lemmas and theorems; while the second part consists of labs, which involve both the manual implementation of algorithms and the learning of built-in tools for efficient analysis of datasets derived from real-world problems. To optimize the understanding of the topics developed and to guide the reader through their studies, the book is organized into chapters, each of which includes an introductory section that reviews the theoretical foundations of statistical inference, followed by a second part with exercises, each accompanied by a comprehensive solution on paper and, when appropriate, using software. This book is aimed at undergraduate students in Statistics, Mathematics, Engineering, and for graduate-level courses in Data Science. 410 0$aLa Matematica per il 3+2,$x2038-5757 ;$v173 606 $aStatistics 606 $aProbabilities 606 $aMathematics 606 $aStatistical Theory and Methods 606 $aProbability Theory 606 $aMathematics 615 0$aStatistics. 615 0$aProbabilities. 615 0$aMathematics. 615 14$aStatistical Theory and Methods. 615 24$aProbability Theory. 615 24$aMathematics. 676 $a519.5 700 $aGasperoni$b Francesca$01065746 701 $aIeva$b Francesca$0517059 701 $aPaganoni$b Anna Maria$0300845 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911007457403321 996 $aExercise Book of Statistical Inference$94389828 997 $aUNINA