I got a set of non-transitive Grime dice from UK enterprise Maths Gear.
I have verified Grime dice with a monte carlo simulation, and calculated probabilities combinatorially, now I’m going to try to verify them experimentally.
The Veritasium chap made a video about Markov Chains. Veritasium outlines Markov’s original text-based experiment. The experiment seems like something that could be educational to duplicate.
What kind of latch or flip-flop is the best analog to my pair of night lights?
Cheap, sensor controlled night lights are available to happy US consumers.
The Wikipedia article on voltage doublers says that a Greinacher circuit works by “following a Villard cell stage with what is in essence a peak detector or envelope detector stage”.
What if you put the peak detector or envelope detector stage after a full wave bridge rectifier? What wave form would result?
I used a 3.3 µF, 370VAC capacitor in a previous Villard Circuit voltage doubler, but I used 67 nF capacitors in a Greinacher Circuit voltage doubler.
That’s a huge capacitance difference. Did I do the Greinacher Circuit correctly?
I got a set of non-transitive Grime dice from UK enterprise Maths Gear.
I built some simple voltage doublers to see what wave forms result.
From Statistics Libre Text:
For samples of size 30 or more, the sample mean is approximately normally distributed, with mean μX = μ and standard deviation σX = σ/√n where n is the sample size. The larger the sample size, the better the approximation.
The above is a pretty typical assertion in statistics texts. The derivation must be a doozy, it’s never shown, and there’s rarely a discussion of the Central Limit Theory itself.
I read an article about Term Frequency-Inverse Document Frequency on John D. Cook Consulting’s blog.
