Visualization: Scatterplot

library(ggplot2)
library(dplyr)

# FALLBACK
if(!exists("raw_data")) {
   raw_data <- data.frame(
    age = rnorm(50, 20, 2),
    anxiety = rnorm(50, 10, 3) + (rnorm(50) * 0.5) 
  )
   # Ensure column names match what we try to plot below
   # In a real app, we'd have a variable selector. 
   # Here we pick the first two numeric cols.
}

# Dynamic Variable Selection for Plotting
num_cols <- names(select(raw_data, where(is.numeric)))
if(length(num_cols) >= 2) {
  x_var <- num_cols[1]
  y_var <- num_cols[2]
  
  ggplot(raw_data, aes(x = .data[[x_var]], y = .data[[y_var]])) +
    geom_point(alpha = 0.6) +
    geom_smooth(method = "lm", se = TRUE, color = "blue") +
    labs(
      title = paste("Scatterplot of", x_var, "by", y_var),
      x = tools::toTitleCase(x_var),
      y = tools::toTitleCase(y_var)
    ) +
    theme_minimal()
} else {
  print("Not enough numeric variables to plot.")
}

Figure 1: Relationship between Variables