Why Most Published Research Findings Are False A Research Paper by John P.A. Ioannidis journals.plos.org There is increasing concern that most current published research findings are false. The probability that a research claim is true may depend on study power and bias, the number of other studies on the same question, and, importantly, the ratio of true to no relationships among the relationships probed in each scientific field. In this framework, a research finding is less likely to be true when the studies conducted in a field are smaller; when effect sizes are smaller; when there is a greater number and lesser preselection of tested relationships; where there is greater flexibility in designs, definitions, outcomes, and analytical modes; when there is greater financial and other interest and prejudice; and when more teams are involved in a scientific field in chase of statistical significance. researchsciencetruth
The value-destroying effect of arbitrary date pressure on code An Article by Gandalf Hudlow iism.org The mandate from above is clear, just get it done! Avoid everything that's in the way: all advice, all expertise, all discovery efforts that detract from hitting the Date™! What these organizations don't realize is that all software change can be modeled as three components: Value, Filler and Chaos. Chaos destroys Value and Filler is just functionality that nobody wants. When date pressure is applied to software projects, the work needed to remove Chaos is subtly placed on the chopping block. Work like error handling, clear logging, chaos & load testing and other quality work is quietly deferred in favor of hitting the Date™. Driving engineers to an arbitrary date is a value destroying mistake agileplanningqualitydiscovery