Sentence examples for statistical mistake from inspiring English sources
The phrase "statistical mistake" is correct and usable in written English.
It can be used when referring to an error or inaccuracy in statistical analysis or data interpretation. Example: "The researchers acknowledged that their findings were flawed due to a significant statistical mistake in their calculations."
As one student remarked after the statistical mistake was pointed out to them, "I thought you only asked for my opinion".
This is to be fair to him, because in Gallup's polling, he had one bad month in the polls which may have been a statistical mistake (an "outlier," as pollsters say), as his numbers recovered the month after and stayed fairly steady for the next six months or so.
The statistical response to the claim that all structural equation models will fail if N is large enough, points to a statistical mistake easily connected to the formula for the model χ test.
It is true that increasing N makes it easier to detect smaller amounts of covariance ill fit as unlikely to be chance sampling artifacts, but it constitutes a statistical mistake to claim that a small amount of observed covariance ill fit says the model contains only small or trivial misspecifications.
Statistical mistakes are widespread.
We found that scientists at the NHS had examined his claims to have detected a leukaemia cluster in north Wales and discovered that they arose from a series of shocking statistical mistakes.
Busby's claims, it seems, were the result of some astonishing statistical mistakes: He counted the overall leukaemia incidence for Wales twice He mixed up the figures from urban areas with those from small rural areas, "trebling the local incidence in north Wales" and creating "spurious clusters in various locations" He claimed there were ten cases of leukaemia in young children in Snowdonia.
The challenge now is to solve new problems and gain new answers – without making the same old statistical mistakes on a grander scale than ever ".
Another of the lab's papers was found, after publication, "to have a statistical analysis mistake that decreased the main significance of the work a lot".
He said the genomics community has also tightened the standard for a "significant" result, precisely to overcome the problem of statistical flukes being mistaken for discoveries.
Phylogenetics, with its hierarchical branching structure, presents a peculiar realm of statistical analysis, where mistaking noise for signal and integrating over uncertainty about nuisance parameters can lead to systematically biased inferences.
