Skip to main content
SpringerLink
Log in

A First Course in Statistical Inference

  • Textbook
  • © 2020

Overview

Authors:
  1. Jonathan Gillard

    1. School of Mathematics, Cardiff University, Cardiff, UK

    View author publications

    You can also search for this author in PubMed   Google Scholar

  • Provides a concise and self-contained introduction to statistical inference for beginning undergraduates
  • Includes over 50 solved exercises and examples, including using R
  • Key concepts and ideas are described in lucid terms without sacrificing mathematical rigor

Part of the book series: Springer Undergraduate Mathematics Series (SUMS)

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
eBook USD 34.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 44.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (7 chapters)

  1. Front Matter

    Pages i-x
    Download chapter PDF

  2. Recap of Probability Fundamentals

    • Jonathan Gillard
    Pages 1-9

  3. Sampling and Sampling Distributions

    • Jonathan Gillard
    Pages 11-33

  4. Toward Estimation

    • Jonathan Gillard
    Pages 35-43

  5. Confidence Intervals

    • Jonathan Gillard
    Pages 45-61

  6. Hypothesis Testing

    • Jonathan Gillard
    Pages 63-90

  7. One-Way Analysis of Variance (ANOVA)

    • Jonathan Gillard
    Pages 91-101

  8. Regression: Fitting a Straight Line

    • Jonathan Gillard
    Pages 103-117

  9. Back Matter

    Pages 119-164
    Download chapter PDF
Back to top

Keywords

About this book

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.

Authors and Affiliations

  • School of Mathematics, Cardiff University, Cardiff, UK

    Jonathan Gillard

About the author

Dr Jonathan Gillard is a Reader in Statistics at Cardiff University, Senior Fellow of the Higher Education Academy, and a member of the Statistics Interest Group of sigma: the UK network for excellence in mathematics and statistics support. He has taught statistical inference to mathematics undergraduates and postgraduates for over 10 years. Jonathan maintains a strong interest in innovative teaching methods, being an editorial board member of MSOR Connections. He is an active researcher of the theory of statistics and is currently working on a number of collaborative projects with the Office for National Statistics and National Health Service. His recent publications have included work on using regression in large dimensions, novel methods for forecasting, and new approaches for learning about the performance of machine learning algorithms.

Bibliographic Information

Publish with us

Policies and ethics

Back to top

Search

Navigation