# How to read a paper: Statistics for the non-statistician. I: Different types of data need different statistical tests

BMJ 1997; 315 doi: http://dx.doi.org/10.1136/bmj.315.7104.364 (Published 9 August 1997)
Cite this as: BMJ 1997;315:364

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1. Trisha Greenhalgh, senior lecturer (p.greenhalgh@ucl.ac.uk)a
1. a Unit for Evidence-Based Practice and Policy, Department of Primary Care and Population Sciences, University College London Medical School/Royal Free Hospital School of Medicine, Whittington Hospital, London N19 5NF

## Introduction

As medicine leans increasingly on mathematics no clinician can afford to leave the statistical aspects of a paper to the “experts.” If you are numerate, try the “Basic Statistics for Clinicians” series in the Canadian Medical Association Journal 1 2 3 4 or a more mainstream statistical textbook.5 If, on the other hand, you find statistics impossibly difficult, this article and the next in this series give a checklist of preliminary questions to help you appraise the statistical validity of a paper.

## Have the authors set the scene correctly?

### Have they determined whether their groups are comparable, and, if necessary, adjusted for baseline differences?

Most comparative clinical trials include either a table or a paragraph in the text showing the baseline characteristics of the groups being studied. Such a table should show that the intervention and control groups are similar in terms of age and sex distribution and key prognostic variables (such as the average size of a cancerous lump). Important differences in these characteristics, even if due to chance, can pose a challenge to your interpretation of results. In this situation, adjustments can be made to allow for these differences and hence strengthen the argument.6

#### Summary points

In assessing the choice of statistical tests in a paper, first consider whether groups were analysed for their comparability at baseline

Does the test chosen reflect the type of data analysed (parametric or non-parametric, paired or unpaired)?

Has a two tailed test been performed whenever the effect of an intervention could conceivably be a negative one?

Have the data been analysed according to the original study protocol?

If obscure tests have been used, do the authors justify their choice and provide a reference?

### What sort of data have they got, and have they used appropriate statistical tests?

Numbers are often used to label the properties of things. We can assign a number to represent our height, weight, and so on. For properties like these, the measurements can be treated as actual numbers. We can, for example, calculate the …

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