A typical journal article contains the results of only one analysis pipeline, by one set of analysts. Even in the best of circumstances, there is reason to think that judicious alternative analyses ...

Bayesian uncertainty analysis represents a powerful statistical framework that integrates prior knowledge with observed measurement data to quantify uncertainty in a consistent probabilistic manner.

Statistical uncertainty in data—or random error in a measurement—particularly when it is used to inform funding and policies, can lead to a variety of issues ...

Analyses of ecological data should account for the uncertainty in the process(es) that generated the data. However, accounting for these uncertainties is a difficult task, since ecology is known for ...

Under growing pressure to report accurate findings as they interpret increasingly larger amounts of data, researchers are finding it more important than ever to follow sound statistical practices.

Journal of Public Administration Research and Theory: J-PART, Vol. 2, No. 3 (Jul., 1992), pp. 333-345 (13 pages) Rational policy analysis confronts the problem of uncertainty directly through various ...

Nate Silver’s FiveThiryEight blog at The New York Times really only does one thing: It makes election predictions. But it does this differently than pretty much everyone else, because it aggregates ...

When you use the statistical analysis features in Excel, you are leveraging one of the most powerful tools available for data manipulation and interpretation. Excel is not just a spreadsheet ...