more examples of creating a basic scatter plot in R using different data and options:

Here are a few more examples of creating a basic scatter plot in R using different data and options:

1. Using the scatterplot() function from the car package to create a scatter plot with a fitted line and a confidence interval:

 Load the car package 
library(car) 
# Create scatter plot with a fitted line and a confidence interval 
scatterplot(x = mtcars$wt, y = mtcars$mpg, xlab = "Weight", ylab = "Miles per Gallon", main = "Scatter Plot of Weight vs Miles per Gallon", smooth = TRUE, reg.line = lm, ci = TRUE)

2. Using the ggplot2 package to create a scatter plot with different shapes and colors for each group of data:

# Load the ggplot2 package 
library(ggplot2) 
 # Create scatter plot with different shapes and colors for each group of data 
ggplot(mtcars, aes(x = wt, y = mpg, shape = factor(cyl), color = factor(cyl))) +
  geom_point() +
  xlab("Weight") +
  ylab("Miles per Gallon") +
  ggtitle("Scatter Plot of Weight vs Miles per Gallon by Number of Cylinders")

3. Using the scatterplotMatrix() function from the car package to create a matrix of scatter plots:

# Load the car package 
library(car) 
# Create a matrix of scatter plots 
scatterplotMatrix(~wt + mpg + hp + drat + qsec, data = mtcars, xlabels = TRUE, ylabels = TRUE, main = "Scatter Plot Matrix of Car Attributes")

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