Many personal transportation-related decisions—such as vehicle purchases—are influenced by life events, like the birth of a child or a change in employment. Modeling tools that reflect how life ...

Count data modelling occupies a central role in statistical applications across diverse disciplines including epidemiology, econometrics and engineering. Traditionally, the Poisson distribution has ...

Despite decades of independent progress in population ecology and movement ecology, researchers have lacked a theoretical bridge between these two disciplines. "Ecologists have been trying to ...

When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...

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 ...

Tech-enabled SaaS growth companies are among the most progressive companies when it comes to making use of data science. In a global survey conducted by McKinsey Analytics in 2020, only 16% of ...

At its heart, data modeling is about understanding how data flows through a system. Just as a map can help us understand a city’s layout, data modeling can help us understand the complexities of a ...