"Confusing correlation with causation is not an unknown issue but it is becoming increasingly problematic as data increases and computers get more powerful… it gets to the heart of what we know – or think we know – about how the world works." correlation is also a topic that Michael Molnar examines in a Forbes article. "Our job is to be skeptical, to dig and understand and poke and prod and to reject the outrageously wrong and if it is not outrageously wrong then to figure out how right it might be so that you can make an educated recommendation." - Avinash KaushikĬausality vs. He encourages readers to look deeper at the data and avoid easy decisions.
Kaushik uses the example above to remind people to be more skeptical of claims that draw bold conclusions from correlated data points. Decisions, opinions, and even business strategies can depend on our ability to tell the difference between them. In our everyday lives, we have access to more data than ever before. However, the data doesn't definitively reveal anything aside from that obvious correlation. There may appear to be a link connecting IQ to ice cream consumption. He points out that there is nothing to ground the causation of one and the other despite a reasonable correlation. Oh, and look there is a red line, what looks like a believable distribution, and a R-squared!"īut Kaushik wants us to think a bit harder about the data at hand, and not take things at face value. "after all this is a reputable site and it is a reputable team. "To normal people (non-Analysts), this graph and article looks legit," wrote Kaushik. Kaushik highlighted an article from The Economist that asserted that eating more ice cream can boost student scores on the PISA reading scale. The correlation and causation examples above show the importance of getting the difference right is critical.Īvinash Kaushik, Digital Marketing Evangelist at Google, wrote in 2016 about how not understanding the difference can be very problematic. causation important?Īpproach your customer experience analytics with confidence Why is knowing the difference between correlation vs.
What is the difference between correlation and causation? In these cases, extra vetting is needed before a correlation can qualify as causation. Although, correlation does not necessarily imply causation, and these examples show the dangers of not understanding the difference between correlation and causation in the real world. More iPhones sold means more people die from falling down the stairs Spending more to see sports matches reduces your likelihood to consume high-fructose corn syrup For example, Harvard Business Review once looked at examples showing the "possibility" that: There are countless articles that share wild, often tongue-in-cheek conclusions as a result of two strongly correlated data sets. One of the biggest confusions during any data analysis revolves around correlation vs. All others must bring data." But too often, data can be misconstrued. Edwards Deming once said, "In God we trust. Data is an extremely powerful element of any decision.
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