This report analyzes NOAA Storm Events data from 1996–2011 to identify which severe weather events are most harmful to population health and which cause the greatest economic damage in the United States. Using R and the tidyverse, the data were cleaned, standardized, and aggregated to ensure consistent event categories. Property and crop damage values were converted from exponent codes to USD, and health impacts were measured by combined fatalities and injuries. The analysis reveals that Tornadoes cause the most injuries, Excessive Heat causes the most fatalities, and Floods produce the largest overall economic losses. Results are presented in two clear figures and supporting tables for use by decision-makers.

Statistika deskriptif sangat berguna dan sangat membantu dalam memahami sebuah data.

Enterprise-level statistical analysis of Texas real estate market using innovative zero-error methodology

Realice un análisis exploratorio de datos (EDA) utilizando el siguiente conjunto de datos disponible en este enlace. El conjunto de datos incluye varias variables médicas predictoras (independientes) y una variable objetivo (dependiente), que es el resultado de interés. Entre las variables independientes se encuentran el número de embarazos de la paciente, el índice de masa corporal (BMI, calculado como peso en kg(altura en m)2 ), el nivel de insulina, la edad, entre otras. En este ejercicio, sustituya todos los valores ausentes o nulos por NAN y realice el análisis correspondiente de los datos faltantes.

by Mrs K Printhan (s3415959) Recommendation: Adjust browser zoom settings to optimise viewing experience

Attempting geom_functions while using nycflights13 data