How should scientists interpret their data? Emerging from their labs after days, weeks, months, even years spent measuring and recording, how do researchers draw conclusions about the results of their experiments? Statistical methods are widely used but
our recent research in Nature Methods reveals that one of the classic science statistics, the P value, may not be as reliable as we like to think.
Scientists like numbers, because they can be compared with other numbers. And often these comparisons are made with statistical analyses, to formalise the process. The broad idea behind all statistical analyses is that they allow the researcher to make somewhat objective assessments of the results of their experiments.
