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A while back someone posted on Reddit about the grading policies of their academic department. Specifically, the department chair made a statement claiming that grades should be Normally distributed with a C average. I responded, claiming that no statistician would ever take the idea that grades follow a Normal distribution seriously. Some asked for context, and I wrote a long response explaining my position. I repeat that argument here, and also give some R code demonstrations showing what curving grades does. Continue reading
Now that we’ve seen MCHT basics, how to make
MCHTest() objects self-contained, and maximized Monte Carlo (MMC) testing with MCHT, let’s now talk about bootstrap testing. Not much is different when we’re doing bootstrap testing; the main difference is that the replicates used to generate test statistics depend on the data we feed to the test, and thus are not completely independent of it. You can read more about bootstrap testing in .
I am very excited to announce my first (public) package (and the second package I’ve ever written, the first being unannounced until the accompanying paper is accepted). That package is MCHT, a package for bootstrap and Monte Carlo hypothesis testing, currently available on GitHub.