If anyone wants to know more about Factor Analysis.. <br><br>FA is used to explain the variation among many measurements of many things. So, if you measure intelligence with 50 different types of tests on 10K people, you may look for 3 factors that explain most of the variation. Those factors aren’t observed, but inferred. When you’re done, you can say something like “I can explain 80% of the variation among the 50 tests using 3 artificially constructed factors.. so those 3 factors must mean something important”. And typically if you inspect them, you find they are correlated with things that make sense. You can also group people based on those factors. <br><br>Richard discusses a powerful factor - the g-factor. When you find something like that, FA really shines. They say, FA has discovered that the "intrinsic dimensionality is low". In other words, something complicated is actually much simpler from a different perspective.,(reply>), "Our science is anti-intellectual by nature. All it can ever do is 'measure things'!" ~ Nietzsche,(reply>), @DF yea it’s exactly like that,(reply>), @Mutual Information I think I understand. It's not very intuitive. It's like decomposing a signal into multiple frequencies, or in this case, some data into a set of probability distributions.,(reply>), @DF not quite, I really mean “inferred”. Meaning you don’t observe them, but you can guess them using some criteria. Those numbers are chosen as those which explain the variation the most. They are selected precisely for that purpose. Then, after the fact, you can try to a figure out a more problem-specific meaning. Like.. “oh this factor looks a lot like genetics.. because people who have a similar amount of that factor tend to come from the same family.”,(reply>), When you say artificially constructed factors, that would mean, for example, some algebraic formula involving age and number of carrots you eat per month?