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Can you identify a trend?

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By Topics | Analytics

So you think you are smarter than the average forecaster, and can identify a trend in time series data?

Graph of time series data

Photo of Nikos Kourentzes
Nikos Kourentzes

You now have a chance to put your trend detection skills (aka trendar) to the test, and help the cause of forecasting research in the process. Nikos Kourentzes, Associate Professor at Lancaster University, is conducting an online experiment on how humans perceive trends compared to statistical forecasting models.

It's fun, and takes just a few minutes. And you can see how your trendar rates against several statistical tests and over 1400 humans who have participated. (Take the experiment)

Four Legs Bad, Two Legs Only Slightly Better

Results so far (1460 participants as of this morning) show humans getting it right slightly over 50% of the time, with the best statistical methods correct on over 90% of the test series.

So our species is only slightly better than chance, or what could be achieved by a sheep. But don't let that get your goat. No four-legged ruminant will ever best us at detecting fashion trends like Moon Boots, Mullets, Fanny Packs, Shoulder Pads, and Puffy Shirts.

Leave Time Series Trend Detection to the Experts

When it comes to finding trends in your time series data, leave it to the experts. When you rely on SAS® Forecast Server, automatic time series diagnosis and modeling will give you more time to pick out that next pair of Crocs.

Tags Nikos Kourentzes SAS Forecast Server trend trendar
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About Author

Mike Gilliland

Product Marketing Manager

Michael Gilliland is a longtime business forecasting practitioner and formerly a Product Marketing Manager for SAS Forecasting. He is on the Board of Directors of the International Institute of Forecasters, and is Associate Editor of their practitioner journal Foresight: The International Journal of Applied Forecasting. Mike is author of The Business Forecasting Deal (Wiley, 2010) and former editor of the free e-book Forecasting with SAS: Special Collection (SAS Press, 2020). He is principal editor of Business Forecasting: Practical Problems and Solutions (Wiley, 2015) and Business Forecasting: The Emerging Role of Artificial Intelligence and Machine Learning (Wiley, 2021). In 2017 Mike received the Institute of Business Forecasting's Lifetime Achievement Award. In 2021 his paper "FVA: A Reality Check on Forecasting Practices" was inducted into the Foresight Hall of Fame. Mike initiated The Business Forecasting Deal blog in 2009 to help expose the seamy underbelly of forecasting practice, and to provide practical solutions to its most vexing problems.

1 Comment

  1. Nikos Kourentzes on

    Thanks for publicizing the experiment! I will post some preliminary results at my blog, once I have adequate sample. I am sure you will find them interesting - so far they are somewhat surprising for me! Nikos

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