A mathematical ritual known as null hypothesis significance testing has led researchers astray since the 1950s.
Some journals now require investigators to fork over their research designs and experimental data before submitting research papers for peer review. The goal is to discourage data fudging and to up the odds of publishing results that can be confirmed by other researchers.Percentage of ‘landmark’ cancer studies that a biotechnology firm was able to replicate over a decade But the real problem lies in the null ritual itself, Gigerenzer says.
One inspiration for the null ritual came from British statistician Ronald Fisher. Starting in the 1930s, Fisher devised a type of significance testing to analyze the likelihood of a null hypothesis, which a researcher could propose as either an effect or no effect. Fisher wanted to calculate the exact statistical significance associated with, say, using a particular fertilizer deemed promising for crop yields.
Psychologists’ null ritual folded elements of both approaches into a confusing hodge-podge. Researchers often don’t realize that statistically significant results don’t prove that a true effect has been discovered.. A closer analysis may reveal findings consistent with a real effect, especially when the original results fell just short of the arbitrary cutoff for statistical significance.
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