i work as a software engineer and dont deal with statistics often. i ran into an incident mentioned below and it made me look for a book that helps me understand the principles of statistics and helps me learn how to apply them . incident- i was working on upgrading "ffmpeg" library used in one our video-processing systems and was looking for a test suite to catch regressions. i did not have a representative test dataset that gives coverage across inputs my system gets and i lacked the expertise required to define a set of dimensions across which i should collect test cases to from a dataset. when i expressed this issue, i was advised to do "shadow testing" by running the old and upgraded system on same customer traffic of N days and compare the results. when i probed for the reason, the response was that shadow testing allows running the upgraded system on a large sample of data that's more likely to be representative of system's inputs and it made sense! - (broadly, this suggestion is an intuitive application of sampling.)

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