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# A borderline definite marginally mild notably numerically increasing suggestively verging on significant result

Matthew Hankins over at *Psychologically Flawed* has harvested an amusing list of quotes from studies that failed to find a significant result:

a borderline significant trend (p=0.09) |

a clear trend (p<0.09) |

a clear, strong trend (p=0.09) |

a decreasing trend (p=0.09) |

a definite trend (p=0.08) |

a favorable trend (p=0.09) |

a favourable statistical trend (p=0.09) |

a little significant (p<0.1) |

a marginal trend (p=0.09) |

a marked trend (p=0.07) |

a mild trend (p<0.09) |

a near-significant trend (p=0.07) |

a negative trend (p=0.09) |

a nonsignificant trend (p<0.1) |

a notable trend (p<0.1) |

a numerical increasing trend (p=0.09) |

a numerical trend (p=0.09) |

a positive trend (p=0.09) |

a possible trend (p=0.09) |

a pronounced trend (p=0.09) |

a reliable trend (p=0.058) |

a significant trend (p=0.09) |

a slight trend (p<0.09) |

a slightly increasing trend (p=0.09) |

a small trend (p=0.09) |

a statistical trend (p=0.09) |

a strong trend (p=0.077) |

a suggestive trend (p=0.06) |

a weak trend (p=0.09) |

a weak trend (p=0.09) |

a worrying trend (p=0.07) |

all but significant (p=0.055) |

almost became significant (p=0.06) |

almost but not quite significant (p=0.06) |

almost reached statistical significance (p=0.06) |

almost significant (p=0.06) |

almost significant tendency (p=0.06) |

almost statistically significant (p=0.06) |

an associative trend (p=0.09) |

an expected trend (p=0.08) |

an increasing trend (p<0.09) |

an inverse trend toward signiﬁcance (p=0.06) |

an observed trend (p=0.06) |

an unexpected trend (p=0.09) |

an unexplained trend (p=0.09) |

approached acceptable levels of statistical significance (p=0.054) |

approached but did not quite achieve significance (p>0.05) |

approached but fell short of significance (p=0.07) |

approached conventional levels of significance (p<0.10) |

approached near significance (p=0.06) |

approached our criterion of significance (p>0.08) |

approached significant (p=0.11) |

approached the borderline of significance (p=0.07) |

approached the level of signiﬁcance (p=0.09) |

approached trend levels of significance (p0.05) |

approached, but did reach, significance (p=0.065) |

approaches but fails to achieve a customary level of statistical significance (p=0.154) |

approaches statistical significance (p>0.06) |

approaching significance (p=0.09) |

approximately significant (p=0.053) |

approximating significance (p=0.09) |

arguably significant (p=0.07) |

as good as significant (p=0.0502) |

at the brink of significance (p=0.06) |

at the cusp of significance (p=0.06) |

at the edge of significance (p=0.055) |

at the margin of significance (p=0.056) |

at the margin of statistical significance (p<0.07) |

at the very edge of significance (p=0.053) |

barely significant (p=0.07) |

better trends of improvement (p=0.056) |

bordered on a statistically significant value (p=0.06) |

bordered on being significant (p>0.07) |

bordered on being statistically significant (p=0.0502) |

bordered on but was not less than the accepted level of significance (p>0.05) |

bordered on significant (p=0.09) |

borderline level of statistical significance (p=0.053) |

borderline signiﬁcant (p=0.09) |

close to a marginally significant level (p=0.06) |

close to being significant (p=0.06) |

close to being statistically signiﬁcant (p=0.055) |

close to borderline signiﬁcance (p=0.072) |

close to the boundary of significance (p=0.06) |

closely approaches the brink of signiﬁcance (p=0.07) |

closely approaches the statistical significance (p=0.0669) |

closely approximating significance (p>0.05) |

closely significant (p=0.058) |

close-to-signiﬁcant (p=0.09) |

did not quite achieve acceptable levels of statistical significance (p=0.054) |

did not quite achieve significance (p=0.076) |

did not quite achieve the conventional levels of significance (p=0.052) |

did not quite achieve the threshold for statistical significance (p=0.08) |

did not quite attain conventional levels of significance (p=0.07) |

did not quite reach a statistically significant level (p=0.108) |

did not quite reach statistical significance (p=0.063) |

did not reach the traditional level of signiﬁcance (p=0.10) |

did not reach the usually accepted level of clinical significance (p=0.07) |

difference was apparent (p=0.07) |

direction heading towards significance (p=0.10) |

does not reach the conventional significance level (p=0.098) |

effectively significant (p=0.051) |

essentially significant (p=0.10) |

extremely close to signiﬁcance (p=0.07) |

failed to reach significance on this occasion (p=0.09) |

failed to reach statistical significance (p=0.06) |

fairly close to significance (p=0.065) |

fairly significant (p=0.09) |

falls just short of standard levels of statistical significance (p=0.06) |

fell barely short of significance (p=0.08) |

fell just short of statistical significance (p=0.12) |

fell narrowly short of significance (p=0.0623) |

fell only marginally short of significance (p=0.0879) |

felt short of significance (p=0.07) |

flirting with conventional levels of significance (p>0.1) |

heading towards significance (p=0.086) |

highly significant (p=0.09) |

hint of significance (p>0.05) |

hovered around signiﬁcance (p = 0.061) |

hovered at nearly a significant level (p=0.058) |

hovering closer to statistical significance (p=0.076) |

hovers on the brink of significance (p=0.055) |

in the edge of significance (p=0.059) |

inconclusively significant (p=0.070) |

indeterminate significance (p=0.08) |

indicative significance (p=0.08) |

just about significant (p=0.051) |

just above the margin of significance (p=0.053) |

just barely below the level of significance (p=0.06) |

just barely insignificant (p=0.11) |

just beyond significance (p=0.06) |

just escaped significance (p=0.07) |

just failed significance (p=0.057) |

just failed to be significant (p=0.072) |

just failed to reach statistical significance (p=0.06) |

just failing to reach statistical significance (p=0.06) |

just fails to reach conventional levels of statistical significance (p=0.07) |

just lacked significance (p=0.053) |

just missed being statistically significant (p=0.06) |

just missing significance (p=0.07) |

just over the limits of statistical significance (p=0.06) |

just short of significance (p=0.07) |

just shy of significance (p=0.053) |

just skirting the boundary of significance (p=0.052) |

just tottering on the brink of significance at the 0.05 level |

leaning towards significance (p=0.15) |

leaning towards statistical significance (p=0.06) |

loosely significant (p=0.10) |

marginal significance (p=0.07) |

marginally insignificant (p=0.08) |

marginally nonsignificant (p=0.096) |

marginally significant (p>=0.1) |

marginally significant tendency (p=0.08) |

marginally statistically significant (p=0.08) |

may not be signiﬁcant (p=0.06) |

mildly signiﬁcant (p=0.07) |

moderately significant (p>0.11) |

modestly significant (p=0.09) |

near limit significance (p=0.073) |

near miss of statistical significance (p>0.1) |

near nominal significance (p=0.064) |

near significance (p=0.07) |

near to statistical significance (p=0.056) |

near/possible significance(p=0.0661) |

near-borderline significance (p=0.10) |

near-certain signiﬁcance (p=0.07) |

nearly approaches statistical significance (p=0.079) |

nearly borderline significance (p=0.052) |

nearly reached a significant level (p=0.07) |

nearly reaching the level of significance (p<0.06) |

nearly significant (p=0.06) |

nearly significant tendency (p=0.06) |

nearly, but not quite significant (p>0.06) |

near-marginal significance (p=0.18) |

near-significant (p=0.09) |

near-to-significance (p=0.093) |

near-trend significance (p=0.11) |

nominally significant (p=0.08) |

non-insignificant result (p=0.500) |

non-significant in the statistical sense (p>0.05 |

not absolutely significant but very probably so (p>0.05) |

not as significant (p=0.06) |

not clearly significant (p=0.08) |

not completely significant (p=0.07) |

not conventionally significant (p=0.089), but.. |

not currently significant (p=0.06) |

not decisively significant (p=0.106) |

not entirely significant (p=0.10) |

not exactly significant (p=0.052) |

not formally significant (p=0.06) |

not fully significant (p=0.085) |

not highly significant (p=0.089) |

not insignificant (p=0.056) |

not markedly significant (p=0.06) |

not non-significant (p>0.1) |

not numerically significant (p>0.05) |

not overly significant (p>0.08) |

not quite borderline significance (p>=0.089) |

not quite reach the level of significance (p=0.07) |

not quite significant (p=0.118) |

not quite within the conventional bounds of statistical significance (p=0.12) |

not reliably signiﬁcant (p=0.091) |

not significant by conventional standards (p=0.10) |

not significant in the narrow sense of the word (p=0.29) |

not significantly significant but..clinically meaningful (p=0.072) |

not strictly significant (p=0.06) |

not strictly speaking significant (p=0.057) |

not strongly significant (p=0.08) |

not technically significant (p=0.06) |

not that significant (p=0.08) |

not too distant from statistical significance at the 10% level |

not too far from significant at the 10% level |

not totally significant (p=0.09) |

not very definitely significant (p=0.08) |

not very significant (p=0.1) |

not wholly significant (p>0.1) |

not yet significant (p=0.09) |

noticeably signiﬁcant (p=0.055) |

on the boundary of signiﬁcance (p=0.055) |

on the brink of significance (p=0.052) |

on the cusp of conventional statistical significance (p=0.054) |

on the cusp of significance (p=0.058) |

on the edge of significance (p>0.08) |

on the limit to significant (p=0.06) |

on the margin of significance (p=0.051) |

only a little short of significance (p>0.05) |

only just insignificant (p>0.10) |

only just missed significance at the 5% level |

only slightly less than significant (p=0.08) |

only slightly non-signiﬁcant (p=0.0738) |

partial significance (p>0.09) |

partially significant (p=0.08) |

partly significant (p=0.08) |

possibly significant (0.05<p>0.10) |

potentially significant (p>0.1) |

practically significant (p=0.06) |

probably not significant (p>0.25) |

provisionally significant (p=0.073) |

quasi-significant (p=0.09) |

quite close to significance at the 10% level (p=0.104) |

quite significant (p=0.07) |

rather marginal significance (p>0.10) |

reached near significance (p=0.07) |

reasonably significant (p=0.07) |

remarkably close to significance (p=0.05009) |

resides on the edge of significance (p=0.10) |

roughly significant (p>0.1) |

scarcely significant (0.05<p>0.1) |

significant at the .07 level |

significant tendency (p=0.09) |

significant to some degree (0<p>1) |

significant, or close to significant effects (p=0.08, p=0.05) |

significantly better overall (p=0.051) |

significantly significant (p=0.065) |

similar but not nonsigniﬁcant trends (p>0.05) |

slight non-significance (p=0.06) |

slight significance (p=0.128) |

slight tendency toward significance (p=0.086) |

slightly exceeded signiﬁcance level (p=0.06) |

slightly failed to reach statistical signiﬁcance (p=0.061) |

slightly insignificant (p=0.07) |

slightly marginally significant (p=0.06) |

slightly significant (p=0.09) |

somewhat marginally significant (p>0.055) |

somewhat short of significance (p=0.07) |

somewhat significant (p=0.23) |

strong trend toward significance (p=0.08) |

sufficiently close to significance (p = 0.07) |

suggestive of a significant trend (p=0.08) |

suggestive of statistical significance (p=0.06) |

suggestively significant (p=0.064) |

tantalisingly close to significance (p=0.104) |

teetering on the brink of significance (p=0.06) |

tend to significant (p>0.1) |

tended to approach significance (p=0.09) |

tended to be significant (p=0.06) |

tended toward significance (p=0.13) |

tendency toward significance (p approaching 0.1) |

tendency toward statistical significance (p=0.07) |

tends to approach signiﬁcance (p=0.12) |

tentatively signiﬁcant (p=0.107) |

too far from signiﬁcance (p=0.12) |

trend bordering on statistical significance (p=0.066) |

trend in a significant direction (p=0.09) |

trend in the direction of significance (p=0.089) |

trend toward (p>0.07) |

trending towards significance (p>0.15) |

trending towards significant (p=0.099) |

uncertain significance (p>0.07) |

vaguely significant (p>0.2) |

verging on significance (p=0.056) |

very close to significant (p=0.11) |

very closely approaches the conventional significance level (p=0.055) |

very nearly significant (p=0.0656) |

very slightly non-significant (p=0.10) |

virtually significant (p=0.059) |

weak significance (p>0.10) |

weak trend toward significance (p=0.12) |

weakened..significance (p=0.06) |

weakly non-significant (p=0.07) |

weakly significant (p=0.11) |

well-nigh signiﬁcant (p=0.11) |

We can umm and ahh all day about how to describe a not significant result and where words begin to become misleading but the important thing is that these studies were published and didn’t disappear into the file drawer.

For a great set of further reading on the topic check out Chris Chambers’ lecture slides from a lecture a couple of days ago at Sussex University. Also in case you missed it, check out my post from earlier this week The Mystery of the Missing Experiments which seems to be generating a somewhat fascinating discussion in the comments.

*To keep up to date with this blog you can follow Neurobonkers on Twitter, Facebook, Google+, RSS or join the mailing list.*

*Image Credit: Shutterstock/Anisha Creations*

## What early US presidents looked like, according to AI-generated images

"Deepfakes" and "cheap fakes" are becoming strikingly convincing — even ones generated on freely available apps.

- A writer named Magdalene Visaggio recently used FaceApp and Airbrush to generate convincing portraits of early U.S. presidents.
- "Deepfake" technology has improved drastically in recent years, and some countries are already experiencing how it can weaponized for political purposes.
- It's currently unknown whether it'll be possible to develop technology that can quickly and accurately determine whether a given video is real or fake.

### The future of deepfakes

<p>In 2018, Gabon's president Ali Bongo had been out of the country for months receiving medical treatment. After Bongo hadn't been seen in public for months, rumors began swirling about his condition. Some suggested Bongo might even be dead. In response, Bongo's administration released a video that seemed to show the president addressing the nation.</p><p>But the <a href="https://www.facebook.com/watch/?v=324528215059254" target="_blank">video</a> is strange, appearing choppy and blurry in parts. After political opponents declared the video to be a deepfake, Gabon's military attempted an unsuccessful coup. What's striking about the story is that, to this day, experts in the field of deepfakes can't conclusively verify whether the video was real. </p><p>The uncertainty and confusion generated by deepfakes poses a "global problem," according to a <a href="https://www.brookings.edu/research/is-seeing-still-believing-the-deepfake-challenge-to-truth-in-politics/#cancel" target="_blank">2020 report from The Brookings Institution</a>. In 2018, the U.S. Department of Defense released some of the first tools able to successfully detect deepfake videos. The problem, however, is that deepfake technology keeps improving, meaning forensic approaches may forever be one step behind the most sophisticated forms of deepfakes. </p><p>As the 2020 report noted, even if the private sector or governments create technology to identify deepfakes, they will:</p><p style="margin-left: 20px;">"...operate more slowly than the generation of these fakes, allowing false representations to dominate the media landscape for days or even weeks. "A lie can go halfway around the world before the truth can get its shoes on," warns David Doermann, the director of the Artificial Intelligence Institute at the University of Buffalo. And if defensive methods yield results short of certainty, as many will, technology companies will be hesitant to label the likely misrepresentations as fakes."</p>The COVID-19 pandemic has introduced a number of new behaviours into daily routines, like physical distancing, mask-wearing and hand sanitizing. Meanwhile, many old behaviours such as attending events, eating out and seeing friends have been put on hold.

## VR experiments manipulate how people feel about coffee

A new study looks at how images of coffee's origins affect the perception of its premiumness and quality.

- Images can affect how people perceive the quality of a product.
- In a new study, researchers show using virtual reality that images of farms positively influence the subjects' experience of coffee.
- The results provide insights on the psychology and power of marketing.

## Is empathy always good?

Research has shown how important empathy is to relationships, but there are limits to its power.