This important study introduces a Bayesian method to determine bacterial counts that accounts for the experimental noise inherent to dilution and plating methods, and distinguishes it from biological ...

When organizations do marketing research they will collect a lot of information some of it will be hard data called quantitative data, while soft data is termed qualitative data. Here we go ...

Common Data Set The Common Data Set (CDS) initiative is a collaborative effort among institutional researchers and guidebook publishers, as represented by the College Board, Peterson's, and U.S. News ...

For months, the research community has been racing to download and store thousands of demographic data sets the government wants to delete because they don’t align with the Trump administration’s ...

Early drafts suggest regulators are interested in the opacity of AI training sets and may impose disclosure or opt-out requirements even where de-identified data is used.

The Bureau of Labor Statistics is cutting back its collection of data on consumer prices, raising questions about the reliability of federal economic statistics under President Trump. Every month ...

Qualitative research uncovers the “why” Using methods like interviews, focus groups and ethnography, qualitative research seeks to answer the “why” and “how” behind people’s experiences and behavior.

Objective Data are essential for tracking and monitoring of progress on health-related sustainable development goals (SDGs). But the capacity to analyse subnational and granular data is limited in low ...

The U.S. Government collects and maintains a database of nearly 200,000 data sets - free and open for public use. You can find data relating to health, energy, climate, manufacturing and many other ...

Qualitative data can also be collected in a number of other ways, including interviews, panel groups, ethnography (participant observation), archival work, and document analysis.

Nvidia has acquired synthetic data startup Gretel to bolster the AI training data used by the chip maker's customers and developers.

The data set was randomly split into training, validation, and held-out test subsets (80%, 10%, and 10%, respectively) such that all views from any single patient were restricted to a single subset.