Users can instantly recreate AI-generated insights in their existing BI and data analytics tools and use Collections to organize multiple insights around business initiatives OAKLAND, CA, Dec. 13, ...

Identifying outliers in a data set is conceptually cut and dry. Extremes, by definition, should be conspicuous. But in practice, labeling outliers is a mix of art and science, in part because ...

In several cases, when the one-year performance is close to or reaches the outlier, this point marks an extreme return that begins to reverse. When the S&P 500 one-year return briefly exceeded 70% in ...

Outliers deviate from the norm—significantly enough to give marketers pause. But outliers can tell us more about our data, how we gather it, and what is in it, if we examine the entire data set ...

This paper analyzes the resampling technique of jackknifing and its capability of detecting outliers in data envelopment analysis. It is well recognized that measured efficiency is sensitive to ...

Earlier this week, the Democratic race for president was seemingly rocked by a Monmouth University poll showing former Vice President Joe Biden falling from 32% to 19%. The poll, which had Biden in a ...

OAKLAND, Calif., Dec. 13, 2021 (GLOBE NEWSWIRE) -- Outlier AI, the leading automated business analysis (ABA) platform, today released new features that enable users to move from automated AI-generated ...

In recent updates to this series (see list below) I’ve been looking at various methodologies to identify extreme values in a time series, such as the S&P 500 Index. One motivation for this analysis is ...