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DataProducts module4 project
Project assignment of couse of same name
Assignment 11 Code Approach
epi553_hw03_Frimpong_Marina
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.
SPC: SQC I-MR Chart Report
An SQC I-MR Control Chart Pair for Potassium Concentration in Municipal Water
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Guía_ShinyApp_desde_Cero
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R_tips_quarto发布到github
记录如何使用quarto创建个人知识图书,并将其发布到github的静态网页
Modulo 2 - Parcial 2
PAF 516 Final Dashboard