Fuzzy regression models extend traditional statistical regression by integrating fuzzy set theory to better handle imprecision and uncertainty inherent in many real-world data sets. These models ...

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 ...

When you perform regression analysis in Microsoft Excel, you are engaging in a statistical process that helps you understand the relationship between variables. This technique is particularly useful ...

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 ...

A behind-the-scenes blog about research methods at Pew Research Center. For our latest findings, visit pewresearch.org. Many of Pew Research Center’s survey analyses show relationships between two ...

We present self-modeling regression models for flexible nonparametric modeling of multiple outcomes measured longitudinally. Based on penalized regression splines, the models borrow strength across ...

When you use the statistical analysis features in Excel, you are leveraging one of the most powerful tools available for data manipulation and interpretation. Excel is not just a spreadsheet ...