3 ms·
Central limit theorem tells in practice that gaussian distributions is can be expected to be quite common. And it makes the gaussian distribution a good first g
by jampekka 1y ago
Central limit theorem tells in practice that gaussian distributions is can be expected to be quite common. And it makes the gaussian distribution a good first guess. Least squares gives the ML estimate for gaussian residuals. I don't find this very direct, and there being a rationale doesn't mean that rationale is what in reality drives the usage.
I mention the relation to the gaussian distribution. Which part of the comment is incorrect?
- xadhominemx 1y agoThis part is incorrect: “ The main practical reason why square error is minimized in ordinary linear regression is that it has an analytical solution” OLS is popular because it gives correct answers as a result of the CLT
- disgruntledphd2 1y agoAnd it has an analytical solution, which was important before computing (and still makes it quicker today).
- kyllo 1y agoIn other words, as economists say, because OLS is provably the BLUE (Best Linear Unbiased Estimator) aka the Gauss-Markov Theorem.