Felimban, R. (2025) Financial Prediction Models in Banks: Combining Statistical Approaches and Machine Learning Algorithms.

From the first 5 rows of the dataset, we can see that there are several columns available: species, island, bill_length_mm, bill_depth_mm, flipper_length_mm, body_mass_g, and sex. There also appears ...

It would be super nice in JASP to have the possibility to easy check assumptions through depictions when running a linear regression. This is possible though R: s library “Performance” and using the ...

Linear regression is one of the most used statistical techniques in neuroscience, including the study of the neuropathology of Alzheimer’s disease (AD) dementia. However, the practical utility of this ...

Abstract: Linear regression is the most frequently used regression analysis due to its simplicity in predicting and forecasting. However, because of its parametric approach, it is necessary to test ...

Residuals are an essential part of statistical analysis, especially when testing the validity of a model. They help analysts identify if a model fits the data well or if there are any inconsistencies ...