HW3 for DAT 301

Midterm Exam Objectives Understand the definition and relationship between PDFs and CDFs, including their non-parametric estimators: the empirical distribution function and kernel density estimation (KDE). Estimate sampling distributions using simulation-based methods, specifically the bootstrap. Derive point estimates of parameters using the method of moments and maximum likelihood estimation (MLE). Describe the asymptotic (normal) and bootstrap sampling distributions of maximum likelihood estimators. Apply all the above inferential procedures in a programming environment to perform numerical data analysis.

Homework for Airbnb

This report presents an exploratory data analysis of tuberculosis detection and treatment success rates across provinces in Indonesia. The analysis uses data from the Indonesian Central Bureau of Statistics (BPS) on disease cases by province and type of disease in 2025. Laporan ini menyajikan analisis eksploratif terhadap angka penemuan kasus dan keberhasilan pengobatan tuberkulosis (TBC) di berbagai provinsi di Indonesia. Analisis ini menggunakan data dari Badan Pusat Statistik (BPS) mengenai kasus penyakit menurut provinsi dan jenis penyakit pada tahun 2025.

This report presents an exploratory data analysis of tuberculosis detection and treatment success rates across provinces in Indonesia. The analysis uses data from the Indonesian Central Bureau of Statistics (BPS) on disease cases by province and type of disease in 2025. Laporan ini menyajikan analisis eksploratif terhadap angka penemuan kasus dan keberhasilan pengobatan tuberkulosis (TBC) di berbagai provinsi di Indonesia. Analisis ini menggunakan data dari Badan Pusat Statistik (BPS) mengenai kasus penyakit menurut provinsi dan jenis penyakit pada tahun 2025.