Rochester Institute of Technology researchers are taking on Big Data to reduce the negative impact of faulty measurements in data collected from complex sensing systems. "Based on tremendous ...

Approaches for statistical inference -- The Bayes approach -- Bayesian computation -- Model criticism and selection -- The empirical Bayes approach -- Bayesian design -- Special methods and models -- ...

In a data-driven world, the ability to analyze and interpret information is critical. Harvard University’s Professional ...

The exponentially increasing amounts of data being generated each year make getting useful information from that data more and more critical. The information frequently is stored in a data warehouse, ...

On a lot of DataFrame objects, the index will typically be an ascending list of numbers. If I have something with dates, I ...

Our foray into causal analysis is not yet complete. Until we define the methods of causal inference, we can't get to the deeper insights that causal analysis can provide. This article details many of ...

Elemental analysis methods are used to determine the elemental composition of a substance and the concentration of each element present. However, there are two different subsets: one for determining ...

Magnetic data analysis and inversion techniques represent a critical facet of modern geophysical exploration. These methods involve interpreting magnetic anomalies derived from both ground‐based and ...

EPA will give awards to researchers who come up with innovative ideas for using federally generated toxicity data on chemicals to predict potential health effects. For the past several years, EPA, NIH ...