Big question I always found exploratory tools and confirmatory tools have distinct fans. The fans of exploratory tools believe the conclusion should be data-driven, nothing else beyond data is needed in order to keep object. On the other hand, some confirmatory fans believe that data could provide nothing without context.
Daniel (1988) stated that factor analysis is “designed to examine the covariance structure of a set of variables and to provide an explanation of the relationships among those variables in terms of a smaller number of unobserved latent variables called factors.

This post is a try about how yo simulate lognormal distribution in R. Lognormal distribution is used a lot in cumulative data (e.x. counting), which is very similar with normal distribution except x should be larger than 0. For instance, the number of schools, the number of students. But I always have no idea about how to parameterized this distribution. I’ll update this post as I learn more about lognormal distribution…

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