Nama: Celine Nurhidayah Santoso Kelas: 2024 A NIM: 24031554033 Dosen Pengampu: Moh. Khoridatul Huda, S.Pd., M.Si., Ph.D. Mata Kuliah: Data Mining

Segundo parcial

Project assignment of couse of same name

This assignment uses 2023 BRFSS data (n = 8,000) to identify factors associated with physical health burden among U.S. adults. The outcome is examined two ways: as the number of physically unhealthy days (linear regression) and as a binary indicator of frequent physical distress, 14 or more days in the past 30 (logistic regression) — across 11 predictors including mental health, BMI, general health, depression, exercise, and sociodemographic characteristics. General health status and mental health days were the strongest predictors in both models.

An SQC I-MR Control Chart Pair for Potassium Concentration in Municipal Water

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