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

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

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

iris_mod <- lm(Sepal.Length ~ ., iris)                    # Estimating linear regression

iris_mod <- lm(Sepal.Length ~ ., iris) # Estimating linear regression

install.packages("ggplot2")                               # Install ggplot2 package
library("ggplot2")                                        # Load ggplot2

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)

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")

ggplot(iris_pred, # Drawing plot using ggplot2 aes(x = Pred_Values, y = Obs_Values)) + geom_point() + geom_abline(intercept = 0, slope = 1, color = "cornflowerblue")