Data modeling refers to the architecture that allows data analysis to use data in decision-making processes. A combined approach is needed to maximize data insights. While the terms data analysis and ...

Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision ...

How to use statistical tools for component tolerance analysis. A look at methods such as Monte Carlo and Gaussian distribution. Simulating a dc-dc converter in LTspice to model closed-loop voltage ...

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When you use the statistical analysis features in Excel, you are leveraging one of the most powerful tools available for data manipulation and interpretation. Excel is not just a spreadsheet ...

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

Statistical models predict stock trends using historical data and mathematical equations. Common statistical models include regression, time series, and risk assessment tools. Effective use depends on ...

The data genie is well and truly out of the bottle. The presence of data-driven consultancies, the rise of public data websites and the growth of its use in the media (cough, cough) highlight how ...

Microsoft Excel’s Data Analysis Toolpak is an invaluable add-in for those who require complex statistical or engineering analyses. This powerful feature allows ...

Researchers have created and preliminarily tested what they believe may be one of the first models for predicting who has the highest probability of being resistant to COVID-19 in spite of exposure to ...