BBC Earth (Asia) - - Q & A -

With its cen­tral peak and grace­fully slop­ing sides, the Bell Curve is one of the best­known and im­por­tant graphs in maths and sci­ence. Put sim­ply, it shows the spread of val­ues of any­thing af­fected by the cu­mu­la­tive ef­fects of ran­dom­ness. And there’s no short­age of those: from stock mar­ket jit­ters to hu­man heights and IQ, many phe­nom­ena fol­low at least a rough ap­prox­i­ma­tion of the Bell Curve, with the most com­mon value in the cen­tre, and rarer, more ex­treme val­ues to ei­ther side.

Many text­books re­fer to it as the Gaus­sian Curve, re­flect­ing the fact that the bril­liant 19th-Cen­tury Ger­man math­e­ma­ti­cian Karl Friedrich Gauss de­duced the shape of the curve while study­ing how data are af­fected by ran­dom er­rors. But a French maths teacher named Abra­ham de Moivre ar­rived at the same curve decades ear­lier while tack­ling a prob­lem that had baf­fled math­e­ma­ti­cians for years: how to cal­cu­late the fre­quency that heads or tails appear over the course of many coin-tosses. Most math­e­ma­ti­cians re­fer to the curve sim­ply as the ‘Nor­mal dis­tri­bu­tion’, while his­to­ri­ans of­ten use the term ‘Gaus­sian Curve’ as an ex­am­ple of Stigler’s Law of Eponymy, which states that no sci­en­tific dis­cov­ery is named af­ter its ac­tual dis­cov­erer. RM




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