This chapter introduces the concepts behind age, period and cohort (APC) effects, the data types that can be used to analyse them, and the difficulties in doing so, in particular the identification problem caused by the three variables being exactly collinear. I then introduce the chapters in the book, stating what each asserts we should and shouldn’t do in the analysis of APC. Underlying all the chapters are the same principles: there is no statistical solution to the APC identification problem, we must make strong and clear assumptions to identify linear APC effects, that non-linear APC effects can be estimated but must be carefully interpreted, and that claims to have solved the identification problem mechanically should be viewed with scepticism.