How to use Excel’s Data Model to turn related data into meaningful information Your email has been sent Excel's Data Model feature allows you to build relationships between data sets for easier ...

Statistical modeling continues to deliver distinct value to businesses both independent of, and in concert with, machine learning. “Artificial intelligence” (AI) and “machine learning” are among the ...

A range of genetic factors can influence the onset of diseases like high blood pressure, heart disease, and type 2 diabetes, according to scientists. If we were to know how the DNA influences the risk ...

Responsible AI is an investment in long-term sustainability. The absence of governance can lead to model drift, eroding ...

New release adds global database connections, logical datasources, relational validation and flexible inspections to ...

Data modeling refers to the architecture that allows data analysis to use data in decision-making processes. A combined approach is needed to maximize data insights. While the terms data analysis and ...

Statistical models predict stock trends using historical data and mathematical equations. Common statistical models include regression, time series, and risk assessment tools. Effective use depends on ...

The first step in conducting a regression-based study is to specify a model. In real applications, this is usually the most challenging step - deciding which variables “belong” in the model and which ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

How to use statistical tools for component tolerance analysis. A look at methods such as Monte Carlo and Gaussian distribution. Simulating a dc-dc converter in LTspice to model closed-loop voltage ...