title: “Lab11” author: “Syazwani” date: “2025-06-18” output: pdf_document: toc: true number_sections: true fig_caption: true —

Introduction

This report provides a brief summary of the built-in iris dataset in R using dynamic reporting with Knitr. It includes summary statistics, a simple visualization, and a formatted table.

Summary Statistics

summary(iris)
##   Sepal.Length    Sepal.Width     Petal.Length    Petal.Width   
##  Min.   :4.300   Min.   :2.000   Min.   :1.000   Min.   :0.100  
##  1st Qu.:5.100   1st Qu.:2.800   1st Qu.:1.600   1st Qu.:0.300  
##  Median :5.800   Median :3.000   Median :4.350   Median :1.300  
##  Mean   :5.843   Mean   :3.057   Mean   :3.758   Mean   :1.199  
##  3rd Qu.:6.400   3rd Qu.:3.300   3rd Qu.:5.100   3rd Qu.:1.800  
##  Max.   :7.900   Max.   :4.400   Max.   :6.900   Max.   :2.500  
##        Species  
##  setosa    :50  
##  versicolor:50  
##  virginica :50  
##                 
##                 
## 

Sample Data Table

head(iris, 6) %>%
  kable(caption = "First 6 rows of the iris dataset",
        col.names = c("Sepal Length", "Sepal Width", "Petal Length", "Petal Width", "Species"),
        digits = 2)
First 6 rows of the iris dataset
Sepal Length Sepal Width Petal Length Petal Width Species
5.1 3.5 1.4 0.2 setosa
4.9 3.0 1.4 0.2 setosa
4.7 3.2 1.3 0.2 setosa
4.6 3.1 1.5 0.2 setosa
5.0 3.6 1.4 0.2 setosa
5.4 3.9 1.7 0.4 setosa

Visualization

ggplot(iris, aes(x = Sepal.Length, y = Petal.Length, color = Species)) +
  geom_point(size = 3, alpha = 0.7) +
  labs(
    title = "Sepal Length vs Petal Length",
    subtitle = "Grouped by Species",
    x = "Sepal Length (cm)",
    y = "Petal Length (cm)"
  ) +
  theme_minimal()

Findings

The iris dataset contains measurements of sepal and petal lengths and widths for three different species of flowers. From the summary statistics and plot:

This demonstrates how Knitr enables clean integration of code, output, and narrative in a single document.