This report presents an exploratory data analysis of text datasets including blogs, news, and Twitter data. The analysis includes data loading, basic summaries, sampling, and text preprocessing techniques such as removing punctuation, numbers, and stop words. Word frequency analysis and visualizations are used to understand common patterns in the data. These insights help in preparing the dataset for building a next-word prediction model.

Equipo Kappa — Hannia Salvador · Luz Ruiseñor · Andreu Sarreta · Maximiliano Guevara

I recently applied multiple regression analysis to examine what drives arithmetic performance in a sample of 177 participants. Using a model that included sex, teacher stage, math anxiety, self-efficacy, and personality traits, regression helped isolate the key drivers of performance while controlling for overlapping effects. The strongest and most consistent predictor was **self-efficacy**, followed by a smaller but significant effect of sex. Interestingly, math anxiety, personality (neuroticism), and teacher stage were not significant once other factors were controlled for. The model explained about **17–20% of performance variation**, showing how regression can move beyond correlation to identify the most decision-relevant predictors in complex human data. This is a clear example of how regression modeling supports evidence-based decisions by highlighting what truly matters when multiple factors interact in real-world systems.

Research Paper Draft How Family Violence affects outcomes of CPI investigations.

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