Description

Book Synopsis
"This book makes the task of interpreting statistical findings much more approachable and less daunting for those with little, or no, previous experience, and will provide a valuable reference for the more experienced researcher. I would recommend it to any student undertaking a Nursing Research module."
Conor Hamilton, Student Nurse, Queenâs University Belfast, UK

Need help interpreting other people's health research?

This book offers guidance for students undertaking a critical review of quantitative research papers and will also help health professionals to understand and interpret statistical results within health-related research papers.

The book requires little knowledge of statistics, includes worked examples and is broken into the following sections:

  • A worked example of a published RCT and a health survey
  • Explanations of basic statistical concepts
  • Explanations of common statistical tests
  • A quick guide to statistical terms and conc

    Table of Contents
    Part 1 Worked Examples

    The randomised controlled trial
    The Health survey

    Part 2 Interpreting statistical concepts

    Measuring variables: continuous, ordinal and categorical data
    Describing continuous data: The normal distribution
    Describing nonparametric data
    Measuring concepts: Validity and reliability
    Sampling data: Probability and non-probability samples
    Sample size: criteria for judging adequacy
    Testing hypotheses: what does p actually mean?

    Part 3 Statistical tests

    Introduction to inferential statistics
    Comparing two independent (unrelated) groups: independent (unrelated) t test, Mann-Whitney U test, contingency analysis- Fisher's exact test and Chi-square test
    Comparing three or more independent (unrelated) groups: One-way ANOVA, Kruskal Wallis test and Chi-square test
    Comparing two sets of related data: Matched pairs or single-sample repeated measures- related (paired) t test, Wilcoxon signed rank test, sign test and McNemar's test
    Complex group comparisons: ANOVA / ANCOVA, Friedman two-way ANOVA by ranks and Cochrane Q test
    Simple tests of association: Correlation and linear regression
    complex associations: Multiple and logistic regression

    Part 4 Quick reference guide

    I Framework for statistical review
    II Glossary of terms
    III Guide to statistical symbols
    IV Overview of common statistical tests
    V Guide to the assumptions that underpin statistical tests
    VI Summary of statistical test selection and results
    VII Extracts from statistical tables

Interpreting Statistical Findings A Guide for

Product form

£26.59

Includes FREE delivery

RRP £27.99 – you save £1.40 (5%)

Order before 4pm tomorrow for delivery by Mon 22 Dec 2025.

A Paperback / softback by Jan Walker, Palo Almond

2 in stock


    View other formats and editions of Interpreting Statistical Findings A Guide for by Jan Walker

    Publisher: Open University Press
    Publication Date: 16/07/2010
    ISBN13: 9780335235971, 978-0335235971
    ISBN10: 335235972

    Description

    Book Synopsis
    "This book makes the task of interpreting statistical findings much more approachable and less daunting for those with little, or no, previous experience, and will provide a valuable reference for the more experienced researcher. I would recommend it to any student undertaking a Nursing Research module."
    Conor Hamilton, Student Nurse, Queenâs University Belfast, UK

    Need help interpreting other people's health research?

    This book offers guidance for students undertaking a critical review of quantitative research papers and will also help health professionals to understand and interpret statistical results within health-related research papers.

    The book requires little knowledge of statistics, includes worked examples and is broken into the following sections:

    • A worked example of a published RCT and a health survey
    • Explanations of basic statistical concepts
    • Explanations of common statistical tests
    • A quick guide to statistical terms and conc

      Table of Contents
      Part 1 Worked Examples

      The randomised controlled trial
      The Health survey

      Part 2 Interpreting statistical concepts

      Measuring variables: continuous, ordinal and categorical data
      Describing continuous data: The normal distribution
      Describing nonparametric data
      Measuring concepts: Validity and reliability
      Sampling data: Probability and non-probability samples
      Sample size: criteria for judging adequacy
      Testing hypotheses: what does p actually mean?

      Part 3 Statistical tests

      Introduction to inferential statistics
      Comparing two independent (unrelated) groups: independent (unrelated) t test, Mann-Whitney U test, contingency analysis- Fisher's exact test and Chi-square test
      Comparing three or more independent (unrelated) groups: One-way ANOVA, Kruskal Wallis test and Chi-square test
      Comparing two sets of related data: Matched pairs or single-sample repeated measures- related (paired) t test, Wilcoxon signed rank test, sign test and McNemar's test
      Complex group comparisons: ANOVA / ANCOVA, Friedman two-way ANOVA by ranks and Cochrane Q test
      Simple tests of association: Correlation and linear regression
      complex associations: Multiple and logistic regression

      Part 4 Quick reference guide

      I Framework for statistical review
      II Glossary of terms
      III Guide to statistical symbols
      IV Overview of common statistical tests
      V Guide to the assumptions that underpin statistical tests
      VI Summary of statistical test selection and results
      VII Extracts from statistical tables

    Recently viewed products

    © 2025 Book Curl

      • American Express
      • Apple Pay
      • Diners Club
      • Discover
      • Google Pay
      • Maestro
      • Mastercard
      • PayPal
      • Shop Pay
      • Union Pay
      • Visa

      Login

      Forgot your password?

      Don't have an account yet?
      Create account