Yes, it is worth looking at. My thinking was, how fast did that sequence revert back to the’mean’? It doesn’t take away from the author’s message though.
Reminds me of process I went through to create the charts for my humble grad thesis (1990-ish), by hand, with letter templates and one very expensive rotring pen. Then would transfer the figures to transparencies as backup for my defense. The real presentation was done using a slide projector (this was cutting edge back then, like over-the-top). Yes, took actual photos of my charts..
Yes, in very specific cases where I fully understand the methodology(ies) that is (are) applicable, and am able to verify correct implementation. Also, as an enhanced ‘Google search’ to supplement what I have found. I am the skeptical type… yet, so far have been impressed. But, I wouldn’t trust using AI to blindly give me solutions to a problem I couldn’t solve myself, albeit much more slowly.
Totally agree. Especially for commercial or code that adds value. Writing code is just one element of developing quality, robust, software. In the rea world, commercial or production software must be maintained, supported, and must respond to changing user requirements. The human element is critical, unless you’re OK with relying on LLM’s, crossing your fingers, and have no care to support users.
As much as you all dislike LinkedIn and the cringy posts, keep in mind that for certain parts of the market it is >the< main professional forum. It is where your investors live, and their capital providers live. So, play nice, yeah?
Nicely done.
I have the same challenge with Bayesian stats and usually do not understand why there is such controversy. It isn’t a question of either/or, except in the minds of academics who rarely venture out into the real world, or have to balance intellectual purity with getting a job done.
In the very first example, a practitioner would consciously have to decide (i.e. make the assumption) whether the number of side on the die (n) is known and deterministic. Once that decision is made, the framework with which observations are evaluated and statistical reasoning applied will forever be conditional on that assumption.. unless it is revised. Practitioners are generally OK with that, whether it leads to ‘Bayesian’ or ‘frequentist’ analysis, and move on.