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Let’s say you’re a researcher, data scientist, or analyst and have some time-series data you want to understand what influences it. You can upload it to Likely Spurious and the application will analyze it against our over 1 million datasets, comprised of economic, news ngram, book ngram, health and weather series. We use classic and advanced causal modeling processes, accounting for confounders such as population, inflation, and other patterns which are common causes of spurious associations.