Interpreting Statistical Findings: A Guide for Health Professionals and Students

Jan Walker worked as a health visitor for eight years before taking a degree in psychology and then a PhD which focused pain in later life. Working as a university lecturer and reader, she taught psychology on a wide range of courses for nurses, allied health, medical and social care professionals, from introductory to masters level. She has held honorary contracts with several pain clinics, helping individuals to identify goals and resources for self management. She has conducted, supervised and published research on the lived experience of chronic pain and other chronic conditions. Jan is currently a Visiting Senior Research Fellow at the University of Southampton where she works closely with the Complementary Medicine Research Unit.

Part 1 Worked ExamplesThe 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