Objective: There is limited study on predictive models for live births in patients with polycystic ovarian syndrome (PCOS). The study aimed to develop and validate a nomogram for predicting live ...

Using data to make smart decisions is powerful—but only if you know how to manage the tools behind it. Logistic regression, one of the most widely used methods in data analysis, can be a game-changer ...

\ In the past couple of labs we've learned how to run and interpret linear regression models. Linear regression models are used when your outcome is a continuous numeric variable. But what if you're ...

Gov. Gavin Newsom signs SB 243, the first US law setting child-safety rules for AI chatbots, from crisis redirects to transparency requirements. Hollywood pushes back against OpenAI’s Sora 2 as ...

Abstract: This study tries to detect fake job advertisements online using Novel Logistic Regression and compares its accuracy with linear regression. Data collection and model training are essential ...

choose a suitable regression model for assessing a specific research hypothesis using data collected from an epidemiological study, fit the model using standard statistical software, evaluate the fit ...

ABSTRACT: This extensive research paper delves into the sharing economy, focusing primarily on the popular platform, Airbnb. The sharing economy has become a transformative force in our society, ...

The Statistical Package for the Social Sciences (SPSS) is a powerful software tool that allows you to analyze data efficiently. It is widely used in various fields, including research, survey analysis ...