CreateStatisticalModels.R

# Creating Statistical Model

# Set working directory
setwd("/Users/daviddryburgh/Documents/R_Programming")

# Load CSV file
iris <- read.csv("Iris.csv")

# Peak at data
head(iris)

# Create a scatterplot
plot(
  x = iris$Petal.Length,
  y = iris$Petal.Width,
  main = "Iris Petal Length vs. Width",
  xlab = "Petal Length (cm)",
  ylab = "Petal width (cm)"
)

# Create a linear regression model
model <- lm(
  formula = Petal.Width ~ Petal.Length,
  data = iris
)

# Summarize the model
summary(model)

# Draw a regression line on plot
lines(
  x = iris$Petal.Length,
  y = model$fitted,
  col = "red",
  lwd = 3
)

# Get correlation coefficient
cor(
  x = iris$Petal.Length,
  y = iris$Petal.Width
)

# Predict new values from the model
predict(
  object = model,
  newdata = data.frame(
    Petal.Length = c(2, 5, 7)
  )
)