Studi Kasus: UMKM Dodol Karmina & Asuransi Pertanian Berbasis Curah Hujan Variabel random adalah variabel yang nilainya ditentukan oleh hasil dari suatu percobaan acak. Dalam pemodelan statistika dan simulasi, variabel random digunakan untuk memodelkan fenomena acak di kehidupan nyata. Simulasi variabel random membantu kita memahami distribusi data, menghitung probabilitas, dan membuat prediksi berdasarkan model yang telah dibuat. Pada laporan ini, simulasi variabel random diterapkan pada dua studi kasus nyata: Distribusi Poisson (Diskrit) — kegagalan staples pada proses pengemasan dodol di UMKM Dodol Karmina, Kabupaten Kuningan, Jawa Barat, berdasarkan Sadiah et al. (2024). Distribusi Eksponensial (Kontinu) — curah hujan bulanan di Kecamatan Sidemen, Kabupaten Karangasem, Bali, berdasarkan Qosim, Dharmawan, dan Harini (2018).

Use spatial data, temporal data, and species observation to create a map of Canada Goose migration across Europe in 2025.

Meliputi definisi atau pengenalan Analisis Data Kategori secara umum, kemudian tabel kontingensi, dan ukuran asosiasi. Juga membahas mengenai syntaxnya menggunakan R serta interpretasinya

The time series data that I have chosen to analyze is the Monthly Precipitation in Pennsylvania over a span of 150 years. This data is provided by the [National Centers for Environmental Information](https://www.ncei.noaa.gov/access/monitoring/climate-at-a-glance/statewide/time-series/36/pcp/1/3/1895-2025). The purpose for this data being collected is to track and monitor climate and precipitation trends. This helps support research that is related to weather forecasting and public safety. Since precipitation is a critical variable in studying the ever changing climate, knowing the long term trends in precipitation totals will impact how agriculture, infrastructure, and water sources function. This will help services plan around different events such as droughts, floods, or normal precipitation.