A first course in statistical inference / Jonathan Gillard
Tipo de material:
TextoSeries Springer undergraduate mathematics seriesDetalles de publicación: Cham : Springer, 2020 Descripción: X, 164 páginas ; 24 cmISBN: 9783030395605Tema(s): Estadística | ProbabilidadesResumen: 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.
| Tipo de ítem | Biblioteca de origen | Signatura | Estado | Fecha de vencimiento | Código de barras | Reserva de ítems | Bibliografía recomendada |
|---|---|---|---|---|---|---|---|
| Manuales | 02. BIBLIOTECA CAMPUS PUERTO REAL | 519.2/GIL/fir (Navegar estantería(Abre debajo)) | Disponible Ubicación en estantería | Bibliomaps® | 3745064864 |
INFERENCIA ESTADÍSTICA GRADO EN MATEMÁTICAS Asignatura actualizada 2022-2023 |
Bibliografía. - índice
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.
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