Common mistakes in data presentation and statistical analysis: how can the BioStat Decision Tool help?

As medical and molecular microbiologists who regularly read the scientific literature, it is our impression that many published papers contain data that is inappropriately presented and/or analysed. This is borne out by a number of studies which indicate that typically at least half of published scientific articles that use statistical methods contain statistical errors. While there are an abundance of resources dedicated to explaining statistics to biologists, the evidence would suggest that they are largely ineffective. These resources tend to focus on how particular statistical tests work, with reams of complicated-looking mathematical formulae. In addition, many statisticians are unfamiliar with the application of statistical techniques to molecular microbiology, instead telling us we need more samples, which can be difficult both ethically and practically in fields that include animal work and painstaking sample collection. In an age where performing a statistical test merely requires clicking a button in a computer programme, it could be argued that what the vast majority of biologists need is not mathematical formulae but simple guidance on which buttons to click. We have developed an easy to follow decision chart that guides biologists through the statistical maze. Our practical and user friendly chart should prove useful not only to active researchers, but also to journal editors and reviewers to rapidly determine if data presented in a submitted manuscript has been correctly analysed.