Análise Estatística de 14 Mulheres com Síndrome Genitourinária no Climatério

Creating multiple histograms using ggplot2, to visualize how a variable is distributed across different gropus (Using the inbuilt dataset)

Wearable fitness devices like Jawbone Up, Nike FuelBand, and Fitbit have revolutionized how individuals track their physical activities. While these tools excel at quantifying activity volume, they rarely assess execution quality. This project addresses this gap by analyzing accelerometer data collected from six participants performing barbell lifts.

This analysis investigates the effect of multicollinearity on the estimation of regression coefficients, emphasizing their variability and the dependence between estimation errors.

Recommendation Engines

Demonstrate a R program to construct a box plot showcasing the distribution of a continuous variable, grouped by a categorical variable, using ggplot2

AFTER RH 5 K ALLOCATION

Storms and other severe weather events can cause both public health and economic problems for communities and municipalities. Many severe events can result in fatalities, injuries, and property damage, and preventing such outcomes to the extent possible is a key concern. This report contains the results of an analysis where the goal was to identify the most hazardous weather events with respect to population health and those with the greatest economic impact in the U.S. based on data collected from the U.S. National Oceanic and Atmospheric Administration’s (NOAA). The storm database includes weather events from 1950 through the year 2011 and contains data estimates such as the number fatalities and injuries for each weather event as well as economic cost damage to properties and crops for each weather event. The estimates for fatalities and injuries were used to determine weather events with the most harmful impact to population health. Property damage and crop damage cost estimates were used to determine weather events with the greatest economic consequences.