This stock analysis project systematically examines synthetic market data through basic exploration, key metrics identification, sector performance comparison, company valuation rankings, and feature engineering. Using R's tidyverse, it generates visualizations and statistical tests to uncover market trends, valuation patterns, and sector differences, providing data-driven insights for investment decisions and risk assessment.

Artikel ini berisi tentang Interpretasi Ordinal Logistic Regression pada data Balance Scale

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