These open-source MMM tools solve different measurement problems, from budget optimization to forecasting and preprocessing.
This study proposes an important new approach to analyzing cell-count data, which are often undersampled and cannot be accurately assessed using traditional statistical methods. The case studies ...
Artificial intelligence has developed rapidly in recent years, with tech companies investing billions of dollars in data centers to help train and run AI models. The expansion of data centers has ...
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 ...
Synthetic dataset outputs for public analysis without privacy risk. Part of my current workflow as survey leader of the Data Engineering Pilipinas group. Comparable distributions per column: based on ...
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 ...
Introduction: While imagery practice is effective for performance enhancement, its impact on mental health is inconclusive due to mixed findings and heterogeneous athlete populations. This study aims ...
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 ...
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 ...
Bayesian analysis is being used with increasing frequency in critical care research and brings advantages and disadvantages compared to traditional Frequentist techniques. This study overviews this ...
Gelman, A., Carlin, J.B., Stern, H.S., et al. (2004) Bayesian Data Analysis. 2nd Edition, CRC Press.
ABSTRACT: Stable distributions are well-known for their desirable properties and can effectively fit data with heavy tail. However, due to the lack of an explicit probability density function and ...
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