How statistics lost their power – and why we should fear what comes next

This is an interesting article from The Guardian on “post-truth” politics, where statistics and “experts” are frowned upon by some groups. William Davies shows how statistics in the political debate have evolved from the 17th century until today, where statistics are not regarded as an objective approach to reality anymore but as an arrogant and elitist tool to dismiss individual experiences. What comes next, however, is not the rule of emotions and subjective experience, but privatised data and data analytics that are only available to few anonymous analysts in private corporations. This allows populist politicians to buy valuable insight without any accountability, exactly what Trump and Cambridge Analytica did. The article makes a point how this is troublesome for liberal, representative democracies.


Replicability, Data Quality and Bayesian Methods

On the About page I wrote, that I blog about things I come across while researching for my PhD. So, you may very well ask what this PhD is supposed to be about. For the interested reader — researchers and the uninitiated alike —, here is some overview on my current plans and research focus.

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Scientific Hoaxes and Bad Academic Writing

A new case of scientific hoax, that happened six years ago, is currently circulating:

Six years ago I submitted a paper for a panel, “On the Absence of Absences” that was to be part of an academic conference later that year—in August 2010. Then, and now, I had no idea what the phrase “absence of absences” meant. The description provided by the panel organizers, printed below, did not help. The summary, or abstract of the proposed paper—was pure gibberish, as you can see below. I tried, as best I could within the limits of my own vocabulary, to write something that had many big words but which made no sense whatsoever. I not only wanted to see if I could fool the panel organizers and get my paper accepted, I also wanted to pull the curtain on the absurd pretentions of some segments of academic life. To my astonishment, the two panel organizers—both American sociologists—accepted my proposal and invited me to join them at the annual international conference of the Society for Social Studies of Science to be held that year in Tokyo.

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Mixing up Standard Errors and Standard Deviations

Over at the Non Significance blog, the author describes the case of a paper that has some strange descriptive statistics:

What surprised me were the tiny standard deviations for some of the Variable 1 and 2, especially in combination with the range given.

In the blog post, the author outlines his approach to make sense from the descriptive values. It seems to be likely that the reported Standard Deviations (SD) are actually Standard Errors of the Mean (SEM). I’d like to add to this blog post one argument based on calculus and one argument based on simple simulations to show that SEM’s are indeed much more likely than SD’s.1 Continue reading Mixing up Standard Errors and Standard Deviations

Good Science – Bad Science? Panel Discussion at the University of Cologne

After I found out about the panel discussion on Good Scientific Practice at the University of Cologne via Twitter, I joined yesterday to watch the discussion as it was closely related to my thesis’ topic.

The panel was filled with five professors and one junior professors from different faculties1, whose positions were related to “good vs bad science” in some way.

Continue reading Good Science – Bad Science? Panel Discussion at the University of Cologne

We have more than one Genome

Inspired by a recently published article in the ZEIT (in German only), I did some further reads on the topic of mosaicism. The bottom line: contrary to common belief and what is taught in text books (and University courses), the human body does not consist of cells with a single, personal genome, but instead each cell or cell-cluster has it’s own personal genome. A phenomenon that is also called “mosaicism”.

Until recently we needed a bunch of cells that were used to sequence our DNA, but today we are able to look on our genes on a single-cell basis. Findings now reveal a new theory on how our cells and tissue has evolved and allows for new theories on somatic and psychiatric illnesses.

From a review by Biesecker and Spinner (2013)1:

It has long been known that cancer is a mosaic genetic disorder, but mosaicism is now apparent in a diverse range of other clinical disorders, as indicated by their tissue distributions and inheritance patterns. Recent technical advances have uncovered the causative mosaic variant underlying many of these conditions and have provided insight into the pervasiveness of mosaicism in normal individuals.

This not only changes how we should think about the genetic basis of diseases but also about the genetic basis for personality and “normal” human behavior.

From this findings new theories of genetics and the genetic causes of human differences and diseases will emerge. We are not a single piece of cells with a pre-determined DNA, but a bunch of cells with different and still ongoing mutations in a DNA, that begun with only a single cell. This is fascinating and shows the ever-evolving nature of science and that we have by no means already “discovered everything that can be discovered”.

Further reads