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In Denmark, scientific misconduct is defined as "intention[al] negligence leading to fabrication of the scientific message or a false credit or emphasis given to a scientist", and in Sweden as "intention[al] distortion of the research process by fabrication of data, text, hypothesis, or methods from another researcher's manuscript form or ...
HARKing (hypothesizing after the results are known) is an acronym coined by social psychologist Norbert Kerr [1] that refers to the questionable research practice of "presenting a post hoc hypothesis in the introduction of a research report as if it were an a priori hypothesis".
Note that data dredging is a valid way of finding a possible hypothesis but that hypothesis must then be tested with data not used in the original dredging. The misuse comes in when that hypothesis is stated as fact without further validation. "You cannot legitimately test a hypothesis on the same data that first suggested that hypothesis.
She reports that between the late 1950s and the 1990s, scholars were already expressing concerns about a possible crisis of replication, [51] a suspiciously high rate of positive findings, [52] questionable research practices (QRPs), [53] the effects of publication bias, [54] issues with statistical power, [55] [56] and bad standards of reporting.
Research concerning qigong has been conducted for a wide range of medical conditions, including hypertension, pain and cancer, and with respect to quality of life. [372] Most research concerning health benefits of qigong has been of poor quality, such that it would be unwise to draw firm conclusions at this stage. [374]
Despite skepticism about extreme statements made in the paper, Ioannidis's broader argument and warnings have been accepted by a large number of researchers. [7] The growth of metascience and the recognition of a scientific replication crisis have bolstered the paper's credibility, and led to calls for methodological reforms in scientific research.
In statistical hypothesis testing, this fraction is given the Greek letter α, and 1 − α is defined as the specificity of the test. Increasing the specificity of the test lowers the probability of type I errors, but may raise the probability of type II errors (false negatives that reject the alternative hypothesis when it is true). [a]
The consistent application by statisticians of Neyman and Pearson's convention of representing "the hypothesis to be tested" (or "the hypothesis to be nullified") with the expression H 0 has led to circumstances where many understand the term "the null hypothesis" as meaning "the nil hypothesis" – a statement that the results in question have ...