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

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    A Paperback / softback by Jan Walker, Palo Almond

    1 in stock

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      Publisher: Open University Press
      Publication Date: 16/07/2010
      ISBN13: 9780335235971, 978-0335235971
      ISBN10: 335235972
      Also in:
      Social research and statistics Social services and welfare, criminology

      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

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