Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision-making. In both traditional ...

Statistical modeling lies at the heart of data science. Well-crafted statistical models allow data scientists to draw conclusions about the world from the limited information present in their data. In ...

Longitudinal data analysis encompasses a range of statistical methodologies that examine data collected over extended periods, enabling researchers to disentangle temporal effects and dynamic ...

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 ...

While data is easier than ever to collect and store, knowing what to do with it and how to analyze it is a challenge, especially for those without the proper training. From boosting customer ...

eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...

What are the different types of predictive modeling? Your email has been sent Predictive modeling is a type of data mining that is used in a variety of situations and industries. This process involves ...

Kevin Dayaratna was Director of the Center for Data Analysis and Chief Statistician for Heritage. A variety of statistical tools can detect potential breaches in the integrity of elections. These ...