Statistical significance. Not so… significant!

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In science, the success of an experiment is often determined by a measure called “statistical significance.” A result is considered to be “significant” if the difference observed in the experiment between groups (of people, plants, etc) would be very unlikely if no difference actually exists. The common cutoff for “very unlikely” is that you’d see a difference as big or bigger only 5 percent of the time if it wasn’t really there — a cutoff that might seem, at first sight, very strict.

Statistical significance has been used to draw a bright line between experimental success and failure. Achieving an experimental result with statistical significance often determines if a scientist’s paper gets published or if further research gets funded. That makes the measure far too important in deciding research priorities, statisticians say, and so it’s time to throw it in the trash.

More than 800 statisticians and scientists are calling for an end to judging studies by statistical significance in a comment published in Nature. An accompanying special issue of the American Statistician makes the manifesto crystal clear in its introduction: “‘statistically significant’ — don’t say it and don’t use it.” Science and statistics have never been so simple as to cater to convenient cutoffs. A P value, no matter how small, is just a probability. It doesn’t mean an experiment worked. And it doesn’t tell you if the difference in results between experimental groups is big or small. In fact, it doesn’t even say whether the difference is meaningful.

There is good reason to want to scrap statistical significance. But with so much research now built around the concept, it’s unclear how — or with what other measures — the scientific community could replace it. (1)

All science is based on the probability that something will happen.

But it is the improbable things which shape the cosmos.

The birth of the universe.

The death of a God.

The genesis of a human being…

People living for the wrong things.

People dying for the right ones.

Yes, it is a paradoxical world. Not a sane one.

Stop looking at the probable things.

Look at the clouds. Feel the sun behind them.

There is nothing more dull than the things which happen.

Predicting everything. Knowing it all.

The cornerstone of our civilization.

The cause of our demise.

Can you ever predict anything without knowing everything?

Can you ever know anything without already experiencing everything?

Start looking at the things which will never happen.

And right when you won’t be looking…

You will know they already did!

Knowledge. Destruction.

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Powerful DNA-sequencing techniques have spurred an avalanche of discoveries about ancient humans, but each one comes at a price: the partial destruction of the specimens from which the DNA was taken. Anthropologists Keolu Fox and John Hawks call for researchers to think harder about safeguarding. “Unless some ground rules are established, future scientists, armed with better, potentially less-invasive methods for extracting DNA from ancient samples could well look back on this era as a time of heedless destruction, fuelled by the relentless pressure to publish,” says Fox and Hawks. (1)

We should not be alarmed or surprised though.

Knowledge IS destruction.

Every time we understand something, we dissolve it into pieces.

Every time we get to know something, we forget something else.

The cosmos was once at our fingertips.

Until we tried to touch it.

And it became real…

Seeing better. And better. And better. Until we see nothing at all…

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A few years ago, a team of scientists at EPFL’s Laboratory of Nanoscale Biology, headed by Aleksandra Radenovic in the School of Engineering, developed an algorithm that can estimate a microscope’s resolution in just a few seconds based on a single image. The algorithm’s result indicates how closely a microscope is operating to its full potential. This could be particularly useful for the automated microscopes that have started appearing in research labs. The team’s findings have just been published in Nature Methods.

The scientists used Fourier’s transform as the basis for their algorithm, but they modified it so as to extract as much information as possible from a single image.

The results indicates how closely a microscope is operating to its full potential. The algorithm performs the calculation in just a few seconds and generates a single number. “Researchers can compare this number with the microscope’s maximum possible resolution to see whether the instrument can work even better or modify the experimental conditions and observe how the resolution evolves” says Adrien Descloux, the study’s lead author. (1)

We want to see better. We want to see everything.

So we magnify.

Until we see all the details.

And more.

And more.

And more!

Pushing it to the limit! To see everything!

Until we can distinguish nothing anymore!

Isn’t it funny? The more we analyze the cosmos the more we reach absolute zero. At the end, the point is a circle with zero radius. (source) At the end, in the midst of our greatest triumph, we will see nothing.

Ghosts casting shadows…

In a cosmos without any light…

Except the light we bring on our own…

Virtual ‘universe machine’. Galaxy evolution. Understanding unicorns.

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By creating millions of virtual universes and comparing them to observations of actual galaxies, researchers have made discoveries that present a powerful new approach for studying galaxy formation. (1)

A cosmos full of phenomena. Phenomena we try to understand. Because we imagine we can. A cosmos full of laws. Laws we expect to decipher because we imagine they are there.

Imagine a universe.

And you will understand your own!

What a wonderful place for children!

Imagining unicorns…

Don’t laugh.

They are not your creation.

You are theirs!


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Hallucinations are spooky and, fortunately, fairly rare. But, a new study suggests, the real question isn’t so much why some people occasionally experience them. It’s why all of us aren’t hallucinating all the time.

In the study, Stanford University School of Medicine neuroscientists stimulated nerve cells in the visual cortex of mice to induce an illusory image in the animals’ minds. The scientists needed to stimulate a surprisingly small number of nerve cells, or neurons, in order to generate the perception, which caused the mice to behave in a particular way. (1)

Asking the right question.

But once more, giving the ring answer.

Because even before we start thinking, we have concluded on the answer we want.

Every day more and more evidence arise regarding how easily our perception of the cosmos might be distorted. And yet every day we still insist on us having the right and “correct” (true? What does this even mean?) perception of the cosmos. Because we do not want to accept the obvious. That was always our flaw.

Yes it is easy to hallucinate.

It is easy to fool the mind.

It is easy to see things which should not be seen.

It is not your fault. It is not the cosmos’ fault.

It is just that neither you or the cosmos should care about being here wandering if it’s your fault. Because you actually aren’t here. And there is no fault. That is how all problems start. By seeing a blank piece of paper and yet still wanting to fill it in with every single thought that you make.

Admire that empty piece of paper.

It holds more knowledge than you would ever be able to write down…

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