In today’s data-rich environment, business are always looking for a way to capitalize on available data for new insights and increased efficiencies. Given the escalating volumes of data and the ...

If you’d like an LLM to act more like a partner than a tool, Databot is an experimental alternative to querychat that also works in both R and Python. Databot is designed to analyze data you’ve ...

Dataset: survey ratings (1–10 scale) Target variable: Writing Methods: CUB (in R), Proportional Odds Model (in Python) Goal: Compare model adequacy and interpret ordinal responses ...

Have you ever found yourself wrestling with Excel formulas, wishing for a more powerful tool to handle your data? Or maybe you’ve heard the buzz about Python in Excel and wondered if it’s truly the ...

ABSTRACT: Food insecurity is a global issue, and households in a society can experience food insecurity at different levels that could range from being mildly food insecure to severely food insecure.

What if you could turn Excel into a powerhouse for advanced data analysis and automation in just a few clicks? Imagine effortlessly cleaning messy datasets, running complex calculations, or generating ...

Halva—‘grapHical Analysis with Latent VAriables’—is a Python package dedicated to statistical analysis of multivariate ordinal data, designed specifically to handle missing values and latent variables ...

Jennifer Simonson is a business journalist with a decade of experience covering entrepreneurship and small business. Drawing on her background as a founder of multiple startups, she writes for Forbes ...

The Basics of Returns-Based Style Analysis Fetching Data for Style Analysis Case Study: Looking for Investment Style Drift Unlock More Code Snippets for Rigorous Fund Evaluation Investors choose funds ...

In recent years, high inflation and global conflict busted economist predictions. How well are your funds or portfolios prepared to weather market surprises? Scenario analysis can help portfolio ...