If you have been paying attention to the scientific tabloids (if there is such a thing), the headlines would continually be filled with claims that modern science is having a crisis of confidence. In big bold letters, tabloids would announce there is a REPRODUCIBILITY CRISIS in science. But is all this due to a handful of grumpy scientists who got
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The computer age has seen many advances in science, including how scientists analyse data and report results. While some tools are complex and make it difficult for other scientists to understand exactly what steps were followed, other tools strive to increase the transparency and reproducibility of research. iPython and Jupyter notebooks A new and exciting tool is the electronic notebook.
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Bar and line graphs with standard deviation (SD) or standard error (SE) error bars are often used to visually present continuous data from laboratory studies with small sample sizes. Last year the journal PloS Biology published a paper showing that presenting such data this way is problematic for the following reasons: bar and line graphs conceal how data are distributed
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A recent Nature commentary highlighted a statement by the American Statistical Association on principles to guide the use of p values for interpretation of research findings. The statement was issued out of concern for the lack of understanding of p values and what they imply. Specifically, the 6 principles of the statement are: P values can indicate how incompatible the
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Blind analysis does not refer to closing your eyes, crossing your fingers and hitting GO! on your statistical analysis! In a previous post, I highlighted an article published in Nature on cognitive biases and their impact on reproducible science. Various debiasing techniques have been proposed to tackle this issue, including blind data analysis. This technique was new to me, so
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We all all human. That means we are all prone to bias. In a recent article in Nature entitled How scientists fool themselves – and how they can stop, Regina Nuzzo points out that our skill to fool ourselves may be contributing to the proliferation of non-reproducible research. In science, career advancement depends primarily on the number of published papers,
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Scientifically Sound 