I am looking for "must read"/classical references on data aggregation/disaggregation in statistics, particularly, what they are exactly, why they are done and how statistical measures (media, mean, correlation coefficient, etc.) and indices (Human Development Index, poverty, Gini, etc.) behave under aggregation/disaggregation of data. Is this topic worked out in basic school or undergraduate courses. It seems it is not.
A classic reference is The Future of Data Analysis by John Tukey. This appeared in the Annals of Mathematical Statistics in 1962 and is widely available, for example on JSTOR. I love the beginning sentences: For a long time I have thought I was a statistician, interested in inference from particular to general. But as I have watched mathematical statistics evolve, I have cause to wonder and doubt. Of particular interest for this forum is section 9 of the paper titled "teaching of data analysis." Tukey also authored the book Exploratory Data Analysis in 1977.
Tukey is referred to as "the progenitor of data science," was an intellectual giant of the twentieth century, and was one of the most influential statisticians of the twentieth century. He discovered the ubiquitous Fast Fourier Transform, coined the word "bit," developed the statistical programming language S which begat R, introduced visualizations such as box and whisker plots, $\ldots$