In the previous post we learned that the standard error of a sample statistic indicates how precisely a population parameter is estimated, and the standard error depends on sample size. For a given standard deviation, a small standard error is obtained when sample size is large. The standard error indicates how variable the sample statistic is if the experiment is
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In the previous post we learned that a sample statistic (e.g., a sample mean) is used to estimate a population parameter (e.g., the population mean), and the standard error of the sample statistic indicates the amount of precision around the estimate of the population parameter. A small standard error indicates that a sample statistic estimates a population parameter with high
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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 