Presentation explaining linear regression models

What this gives you: Paired-sample t-test results Wilcoxon signed-rank test results for non-normal data Visual diagnostics (histogram, QQ plot, means + CIs) Effect sizes (Cohen's d) and CIs Summary statistics (mean, median, SD)

This Flexdashboard project in R was designed to visualize key health statistics, focusing on the relationship between Body Mass Index (BMI) and the prevalence of hypertension in the U.S. adult population, stratified by age and sex. Using the Flexdashboard package, we created an interactive dashboard that incorporated summary statistics, scatter plots, box plots and interactive data tables to explore health trends. The analysis utilized dplyr for data manipulation and ggplot2 for visualization, allowing us to observe how higher BMI levels correlate with increased hypertension prevalence, particularly among older adults and males. By stratifying the data, we highlighted significant variations, showing that hypertension rates tend to be higher in older age groups and among males with elevated BMI levels. This project effectively demonstrated the use of R for public health data visualization, providing insights into the impact of obesity on cardiovascular health in the U.S. population.

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