![]() However, whether we have found signal or noise still requires a data quality assessment, as well as an honest assessment of where - and when - we painted the data analytical bull’s-eye. If we look at enough data, then we can usually find data that supports our preconceptions. This happens quite frequently when we are confronted with the challenging signal-to-noise ratio in big data. Perhaps the most predictable malfunction of normal human logic is when clusters of coincidence coincide with what we were looking to find in the data - with the bull’s-eye we drew with our mind’s eye before we started looking at any data. Picking out clusters of coincidence is a predictable malfunction of normal human logic.” With meaning, you overlook randomness, but meaning is a human construction. Looking at the factors from a distance, you can accept the reality of random chance. “If you have a human brain,” McRaney explains, “you do this all of the time. But instead of a bull’s-eye, it is the human eye that’s naturally drawn to any cluster of data points. By painting a bull’s-eye over a cluster of bullet holes, the cowboy places artificial order over natural random chance.”Ī similar issue that sometimes arises during data-driven decision makingis what could be called the Data Sharpshooter Fallacy - when analysts try to overlay meaning onto a random cluster of data points and thereby convince themselves that they have discovered a seemingly magical business insight. ![]() If the cowboy later paints a bull’s-eye over a spot where his bullet holes clustered together, it looks like he is pretty good with a gun. In some places there are lots of them, in others there are few. Over time, the side of the barn becomes riddled with holes. “The fallacy gets its name from imagining a cowboy shooting at a barn. The Texas sharpshooter fallacy (or clustering fallacy) occurs when the same data is used both to construct and test a hypothesis (4) and goes on to explain. In his book You Are Not So Smart, which I am at least smart enough to highly recommend, David McRaney explains the human tendency to interpret patterns in randomness where none actually exist using the example of the Texas Sharpshooter Fallacy.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |