“If you torture the data long enough, it will confess.”
This aphorism, attributed to Ronald Coase, sometimes has been used in a disrespective manner, as if was wrong to do creative data analysis. This view obviously is misleading. In contrast, we at IRET have a much more positive and humanistic view of data management, and therefore we have made this aphorism to our leading guide in difficult times.
We at IRET have made it to our mission to proliferate and foster creative ways of data analysis. Therefore, we proudly introduce an award in recognition of outstanding data creativity: the CREDAM Award. CREDAM is both an acronym (CREative DAta Management), and a statement: credam (lat.) means “I will believe”, or “I will trust”.
This years CREDAM Award goes to …….. the German government!
A new report on poverty in Germany is going to be published soon. What does the data say?
|Year||Overall property in possession of rich households||Overall property in possession of complete lower half|
Seems like a pretty clear picture, and in a previous version of the report, the authors concluded (based on this and other data), that “income disparity increased” (see S√ľddeutsche Zeitung). But that is wrong!! But why is it wrong? Well, that interpretation “does not reflect the opinion of the German government”.
On the pressure of the leader of the minor coalition partner, Philipp R√∂sler (which currently would be elected by 4% of Germans), this conclusion was re-interpreted. Now, the report comes to the completely opposite conclusion: “income disparity decreases“!
As this is a great example of creative data analysis, which liberates us from restrictive and anally retentive “scientific” procedures, we are happy to award the first CREDAM trophy to the German government, especially Phillip R√∂sler. Congratulations!
(Maybe we should think about adopting this strategy for scientific reports as well. Given highly flexible approaches of data analysis, conclusions should rather be based on a majority vote of all (co-)authors and reviewers, not on empirical evidence.)
Dear valued customer,
it is a well-known scientific truth that research results which are accompanied by a fancy, colorful fMRI scan, are perceived as more believable and more persuasive than simple bar graphs or text results (McCabe & Castel, 2007; Weisberg, Keil, Goodstein, Rawson, & Gray, 2008). Readers even agree more with fictitious and unsubstantiated claims, as long as you provide a colorful brain image, and it works even when the subject is a dead salmon.
The power of brain images for everybody
What are the consequence of these troubling findings? The answer is clear. Everybody should be equipped with these powerful tools of research communication! We at IRET made it to our mission to provide the latest, cutting-edge tools for your research analysis. In this case we adopted a new technology called “visually weighted regression” or “watercolor plots” (see here, here, or here), and simply applied a new color scheme.
But now, let’s get some hands on it!
Imagine you invested a lot of effort in collecting the data of 41 participants. Now you find following pattern in 2 of your 87 variables:
You could show that plain scatterplot. But should you do it? Nay. Of course everybody would spot the outliers on the top right. But which is much more important: it is b-o-r-i-n-g!
What is the alternative? Reporting the correlation as text? “We found a correlation of r = .38 (p = .014)”. Yawn.
Or maybe: “We chose to use a correlation technique that is robust against outliers and violations of normality, the Spearman rank coefficient. It turned out that the correlation broke down and was not significant any more (r = .06, p = .708).”.
Don’t be silly! With that style of scientific reporting, there would be nothing to write home about. But you can be sure: we have the right tools for you. Finally, the power of pictures is not limited to brain research – now you can turn any data into a magical fMRI plot like that:
Isn’t that beautiful? We recommend to accompany the figure with an elaborated description: “For local fitting, we used spline smoothers from 10`000 bootstrap replications. For a robust estimation of vertical confidence densities, a re-descending M-estimator with Tukey’s biweight function was employed. As one can clearly see in the plot, there is¬† significant confidence in the prediction of the x=0, y=0 region, as well as a minor hot spot in the x=15, y=60 region (also known as the supra-dextral data region).”
Magical Data Enhancer Tool
With the Magical Data Enhancer Tool (MDET) you can …
- ‚Ä¶ turn boring, marginally significant, or just crappy results into a stunning research experience
- ‚Ä¶ publish in scientific journal with higher impact factors
- ‚Ä¶ receive the media coverage that you and your research deserve
- ‚Ä¶ achieve higher acceptance rates from funding agencies
- ‚Ä¶ impress young women at the bar (you wouldn’t show a plain scatterplot, dude?!)
Q: But – isn’t that approach unethical?
A: No, it’s not at all. In contrast, we at IRES think that it is unethical that only some researchers are allowed to exploit the cognitive biases of their readers. We design our products with a great respect for humanity and we believe that every researcher who can afford our products should have the same powerful tools at hand.
Q: How much does you product cost?
A: The standard version of the Magical Data Enhancer ships for 12’998 $. We are aware that this is a significant investment. But, come on: You deserve it! Furthermore, we will soon publish a free trial version, including the full R code on this blog. So stay tuned!
Lexis “Lex” Brycenet (CEO & CTO Research Communication)
International Research Enhancement Technology (IRET)