Don’t Don’t smooth your data and then use that smoothed data as input to other analysis. You will fool yourself. You will make over-confident decisions. It is the wrong thing to do. […]
Please Don’t Smooth Your (Social Media) Data!
Can We Predict The Unpredictable?
The most intriguing thing about the new peer-reviewed paper of the same name as today’s post in Nature: Scientific Reports by Abbas Golestani and Robin Gras is that it is longer than […]
Don’t Use Statistics Unless You Have To
We’re finally getting it, as evinced by the responses to the article “Netherlands Temperature Controversy: Or, Yet Again, How Not To Do Time Series.” Let’s return to the Screaming Willies. Quoting myself […]
What Is Cause Like?
Time for the two-week teaching sojourn. In order to grasp cause, we need a brief, a very brief, introduction to the Aristotelian metaphysics of change. These are ancient views, largely abandoned in […]
The Four Errors in Mann et al’s “The Likelihood of Recent Record Warmth”
Michael E. Mann and four others published the peer-reviewed paper “The Likelihood of Recent Record Warmth” in Nature: Scientific Reports (DOI: 10.1038/srep19831). I shall call this authors of this paper “Mann” for […]
Time Series And Causality: Global Warming Example
Temperature causes Here is an atmospheric monthly average temperature series: T = (61, 69, 69, 70, 72, 65, 63) (all F). What caused the temperature to take the value T1 = 61? […]
Time Series Aren’t Easy: Tornado Deaths Example
Time series are the most abused statistics in the physical sciences. (It’s an endless, raucous, peer-reviewed contest for the worst in the “soft sciences.”) The Mann problem (is that a typo?) is […]
Paper Claims Surprisingly Strong Link Between Climate Change And Violence. Nonsense.
When does more crime happen, in winter or summer? Why? Too easy. How about this one: according to the FBI, what was the violent crime rate over time? No need to guess. […]
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