This report presents the results of a Chi-Square Test of Independence conducted to examine the association between parent type (mother, father) and uniform design preference (Design A, Design B). The analysis includes a contingency table, test output, and an effect size calculation using Cramér’s V. The results indicate no statistically significant association between the two variables, with a small effect size.

Introduction Data import and initial view Data cleaning (make salary fields numeric) What is the structure and summary of the dataset? How many observations and variables are in the dataset? Count of top job titles and companies (to use as grouping variable) Missing values check Correlation between numeric features Pairwise relationships (scatterplot matrix) Compare distributions of average salary across top job titles Compute summary statistics by job title (top few) Plot relationship between experience and average salary (colored by top job titles) Conclusions and next steps

A dashboard to helpfully visualize theft

This dataset simulates particle collisions at the LHC to identify Higgs boson events. It contains kinematic variables derived from detector measurements and a Target label (s = Signal, b = Background). The aim is to separate rare Higgs decays from common background processes. DER_mass_MMC is a key feature, showing a distinct peak near 125 GeV for Signal events.

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