, Index
S. No. Topic Page No.
1. Exploratory Data Analysis (EDA)
2. Classification Algorithm 1
3. Classification Algorithm 2
4. ICT skills – Calc Spreadsheet
5. Regression Algorithms 1
6. Regression Algorithms 2
7. Unsupervised Learning
, Project 1: EXPLORATORY DATA ANALYSIS (EDA)
Using the iris dataset provided in R Studio, perform a univariate
analysis by creating scatter plots of sepal length, sepal width, petal
length, and petal width.
data(iris) #Load your dataset
head(iris) #View the first few rows
library(ggplot2)
#Sca<er plot for Sepal Length
plot(iris$Sepal.Length, main="Sca<er Plot of Sepal Length", xlab="Index",
ylab="Sepal Length", col="blue", pch=16)
#Sca<er plot for Sepal Width
plot(iris$Sepal.Width, main="Sca<er Plot of Sepal Width", xlab="Index",
ylab="Sepal Width", col="red", pch=16)
S. No. Topic Page No.
1. Exploratory Data Analysis (EDA)
2. Classification Algorithm 1
3. Classification Algorithm 2
4. ICT skills – Calc Spreadsheet
5. Regression Algorithms 1
6. Regression Algorithms 2
7. Unsupervised Learning
, Project 1: EXPLORATORY DATA ANALYSIS (EDA)
Using the iris dataset provided in R Studio, perform a univariate
analysis by creating scatter plots of sepal length, sepal width, petal
length, and petal width.
data(iris) #Load your dataset
head(iris) #View the first few rows
library(ggplot2)
#Sca<er plot for Sepal Length
plot(iris$Sepal.Length, main="Sca<er Plot of Sepal Length", xlab="Index",
ylab="Sepal Length", col="blue", pch=16)
#Sca<er plot for Sepal Width
plot(iris$Sepal.Width, main="Sca<er Plot of Sepal Width", xlab="Index",
ylab="Sepal Width", col="red", pch=16)
