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    Welcome, and The Riddle of the Science Knot!

    January 17, 2020 by

    Welcome! What are we all doing here, you might ask? Well, not to put too fine a point on it: science is broken. And we’re here to fix it! … And by that, I mean that we’re going to meander through a hopelessly bewildering and complex set of issues in order to hopefully enlighten ourselves… Read more

  • INTRO: THE P-HACKING SERIES

    April 2, 2020 by

    Welcome to this exploratory series on the p-hacking phenomenon. P-values are the golden standard for determining if a research study is statistically significant and thus whether it should be published. Timo, my team-mate on this project, has also authored a couple of separate posts on the ‘Bayesian Perspective’ as we look to curate and comment… Read more

  • CLOSING THOUGHTS

    April 2, 2020 by

    WHAT DOES IT ALL MEAN FOR YOU? This series on p-hacking has been very rewarding on a personal level as I feel it’s provided me with a much better understanding of what the research world entails. I hope I’ve been able to convey as much in my writing. If you’re a budding data scientist like… Read more

  • THE P-VALUE MISINTERPRETATION

    April 2, 2020 by

    Why do experienced researchers make this mistake? Simply put p-values are counter intuitive to interpret and suffer from the practice of being described simply! It is very easy to get away with saying to a non-researcher / scientist that p-values require a 0.05 value to demonstrate significance or success in a study.  I posit that… Read more

  • SOLUTIONS TO P HACKING

    April 1, 2020 by

    Thus far we have discussed the principle, the associated problems, the code and the statistics behind the p-value but we have yet to discuss solutions. It is important to remember that although a major part of the replication crisis is the p-value, the tool which enables it, it isn’t 100% responsible.  NEWBIE  I will admit… Read more

  • P-HACKING WITH TALEB

    March 30, 2020 by

    Nassim Nicholas Taleb (profile link) is the inspiration for this blog series, hence the Black Swan Explorations title. His books are best sellers with his unique writing style and often strong and contrarian opinion. I admit to being a fan of his work although I hope to come across more impartial in this post!  I… Read more

  • SERIES REFERENCES

    March 29, 2020 by

    P-HACKING, WHEN AND WHY DID IT ALL START? Why the Father of Modern Statistics Didn’t Believe Smoking Caused Cancer. (n.d.). Retrieved January 12, 2020, from https://priceonomics.com/why-the-father-of-modern-statistics-didnt-believe/ Shafer, G. (n.d.). On the nineteenth-century origins of significance testing and p-hacking. Retrieved December 4, 2019, from http://www.probabilityandfinance.com Not Even Scientists Can Easily Explain P-values | FiveThirtyEight. (n.d.). Retrieved… Read more

  • PRACTICAL P-VALUES

    March 28, 2020 by

    There has been a lot of theoretical discussion thus far on my p-hacking posts which is necessary to get the foundations of a complex subject well understood. But if you are anything like me then you will find a lot of value in practical examples and demonstrations. Even more so if they are interactive. First… Read more

  • WHAT IS A DATA SCIENTIST?

    March 28, 2020 by

    Data and scientist are two words that have been around a long time with crystal clear definitions, yet together they do nothing but cause controversy. This blog aims to dig into the professions purpose and reputation with an eye on what it means for your career. It’s key reading to understanding our blog as it… Read more

  • P-HACKING: WHEN AND WHY DID IT ALL START?

    March 20, 2020 by

    THE HISTORY OF P-HACKING AND IT’S IMPLICATIONS FOR MODERNITY This is Ronald A. Fisher, popularly known as the father of modern statistics looking rather contemplative. The obvious age of the photo is intended to ensure that you, the reader, are aware of quite how long the validity of experimentation has been measured by p-values. In… Read more

  • Python demo: Bayes-Odds Updater

    January 31, 2020 by

    Understanding Evidence, Part 0.5 In order to demonstrate how you can update your beliefs using Bayes theorem as we discussed in the last post, I wrote a simple program in Python. Try it here: Bayesian Belief Manager. First, you have some piece of evidence you want to incorporate into your views. It could be any… Read more

  • The Bayesian Perspective

    January 27, 2020 by

    Understanding Evidence, Part 0. This series aims to give you a deeper understanding of evidence, and its role in the machinery of reasoning. The end goal is that when you’re presented with an argument—or any information-bearing event, really—you’re able to not only tell at a glance whether this represents evidence, but also roughly how much… Read more

  • P-HACKING: It’s a BIG problem

    January 23, 2020 by

    Data dredging, data fishing, data snooping, data butchery have all been used. But P-hacking has won the terminology battle and is a fundamental reason for the ‘reproducibility crisis’ in science. What is it and why is it so important? So what do we mean by P-hacking? P refers to the P value – a figure… Read more

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