This report presents an exploratory data analysis of the U.S. National Oceanic and Atmospheric Administration (NOAA) Storm Database, covering the period from 1950 to 2011. The main goal is to identify which types of severe weather events have the most significant impact on public health (in terms of fatalities and injuries) and which events result in the greatest economic consequences (property and crop damage). The analysis is performed in R using tidyverse packages and includes data transformation, aggregation, and visualization. The results show that tornadoes are the most harmful to population health, while floods, hurricanes, and storm surges lead to the highest economic losses. The report is fully reproducible and includes clearly labeled figures that support the conclusions

Program_01

Bu dosya OLC733 dersi Hafta 4'te işlenen uç değerler konusuna ilişkin öğrenme günlüğünü ve örnek deneme uygulamalarını içermektedir.

this assignment was done by Revalina Putria Hidayat (16231049) for the Intro to Data Science course. the main focus is on visualizing data in R, especially using faceted plots and looking at the proportion of opinions across different regions. basically, it's about making the data easier to understand through graphs. this exercise also covers connecting R to GitHub, so we can track changes, manage versions, and upload the analysis in a more organized way.