R Drawing Predicted vs. Observed Values in ggplot2 Plot (Example Code)

In this article, I’ll illustrate how to draw a plot of predicted vs. observed values in R programming.

Creation of Example Data

data(iris)                                                # Load example data
head(iris)
#   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
# 1          5.1         3.5          1.4         0.2  setosa
# 2          4.9         3.0          1.4         0.2  setosa
# 3          4.7         3.2          1.3         0.2  setosa
# 4          4.6         3.1          1.5         0.2  setosa
# 5          5.0         3.6          1.4         0.2  setosa
# 6          5.4         3.9          1.7         0.4  setosa

Example: Plotting Predicted vs. Observed Values Using the ggplot2 Package

iris_mod <- lm(Sepal.Length ~ ., iris)                    # Estimating linear regression
install.packages("ggplot2")                               # Install ggplot2 package
library("ggplot2")                                        # Load ggplot2
iris_pred <- data.frame(Pred_Values = predict(iris_mod),  # Creating new data
                        Obs_Values = iris$Sepal.Length)
ggplot(iris_pred,                                         # Drawing plot using ggplot2
       aes(x = Pred_Values, y = Obs_Values)) +
  geom_point() +
  geom_abline(intercept = 0, slope = 1,
              color = "cornflowerblue")

r graph figure 1 r drawing predicted vs observed values ggplot2 plot

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