What was the general approach to performing statistics before calculations were fully computerised (i.e. before both calculation and memory were managed by computer)?
I understand the question could become rather broad, so I'm mainly looking for illustrative impressions of the techniques, attitudes and approaches people employed to extract meaning out of data when all you had was a pen, paper and some other mechanical tools.
I suspect that something as simple (to modern statisticians) as linear regression with, say, 100 rows and three variables, would've been rather daunting to someone performing the matrix operations manually. But if an analysis was important, it would've been worth spending the day doing number crunching, or have a room full of human calculators do it for you. But this is still missing a lot of the pre-analysis work (stuff like visualisation, removal of extreme values, etc) that we take for granted today. How would a large regression have been approached back then? What were the shortcuts and clever labour-saving tricks?
I also suspect that many tests (t test, F test, other tests that involve taking a sample of the data) were used much more regularly back then to get a handle on the general feel of the data. Would this be correct?
Finally, were analyses by and large restricted to problems for which analytical solutions could be found?
