The “geom_smooth” Function in R

• Package: ggplot2

• Purpose: To add a smooth curve to a scatter plot for visualizing trends.

• General Class: Geometric object for adding a smoothed conditional mean.

• Required Argument(s):

• mapping: Aesthetic mappings.

• Notable Optional Arguments:

• data: The data to be displayed in this layer.

• method: Smoothing method (e.g., “loess” or “lm”).

• formula: Formula to use in the smoothing method.

• se: Should a confidence interval be drawn around the smooth?

• level: Confidence level of the interval.

• method.args: Additional arguments for the smoothing method.

• n: Number of points to evaluate smooth.

• span: Controls the amount of smoothing.

• degree: The degree of the polynomial for polynomial smoothing.

• family: The family of the generalized additive model (GAM).

• Example:

• # Example usage
  library(ggplot2)
  
  # Create two variables x and y
  x = rnorm(100)
  y = rnorm(100) + 2 * x
  
  # Create a data frame
  my_data <- data.frame(x, y)
  
  # Create a ggplot object with a scatter plot and smoothed curve using geom_smooth
  my_plot <- ggplot(data = my_data, aes(x = x, y = y)) +
  geom_point() +
  geom_smooth(method = "lm", se = FALSE, color = "blue") +
  labs(title = "Scatter Plot with Smoothed Curve", x = "X-axis", y = "Y-axis")
  
  # Print the plot
  print(my_plot)

• In this example, the geom_smooth function from the ggplot2 package is used to add a linear regression line to a scatter plot. The method argument specifies the smoothing method, and se controls whether to include a confidence interval around the smooth.