Introduction Asthma is a chronic respiratory disorder requiring ongoing medical management. This ecological study ...

ZDNET's key takeaways GPT-5.2 barely outperforms GPT-5.1 despite requiring a Plus subscriptionStrong writing and analysis contrast with a disappointing coding regression.New brevity and go signal ...

In Week 11, I explained the difference between anticipated regression and the so-called "Gambler's fallacy", and in Week 12, I talked about retrodiction, or "predicting" the past as a means of testing ...

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

Climate Variability, Sorghum Yield, AquaCrop Model, Gedaref, Sudan, Rain-Fed Agriculture Share and Cite: Hudo, N.A. (2025) Impact of Climate Variability and Change on Sorghum Yield in Gedaref State, ...

A Scientific Reports study developed a pattern neural network that integrates total antioxidant status with clinical and ...

Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...

Objective We performed a systematic review, meta-analysis and meta-regression to determine if dietary protein supplementation augments resistance exercise training (RET)-induced gains in muscle mass ...

Discover a smarter way to grow with Learn with Jay, your trusted source for mastering valuable skills and unlocking your full potential. Whether you're aiming to advance your career, build better ...

Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...

Linear regression is a powerful and long-established statistical tool that is commonly used across applied sciences, economics and many other fields. Linear regression considers the relationship ...