A First Course in Statistical Inference
- Author
- Jonathan Gillard
- Publication Year
- 2020
- Publisher
- Springer
- Language
- English
- Document Type
- Book
- Faculty / Subject Heading
- Computer Science
- Download Book Read 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.
Keywords: Mathematics and Statistics / Statistical inference / Confidence interval / Hypothesis testing / Distribution theory / Data science / R / Statistical Theory and Methods / Statistics and Computing / Statistics Programs
