title: “Correlation Analysis Report” author: “Your Name” date: “2024-03-05” # Load the data from the CSV file data <- read.csv(“cat.csv”)

Check for missing values

summary(data)

Calculate the correlation coefficient (Pearson’s correlation)

correlation <- cor(data\(CDI, data\)PDI)

Create the document title and heading

title <- “Correlation Analysis Report” heading <- “Correlation between CDI and PDI”

Print the correlation coefficient with a descriptive label

cat(“”, title, ””) cat(“##”, heading, “:”, round(correlation, digits = 3))

Geography CDI PDI
Length:64 Min. : 49.0 Min. : 0.0
Class :character 1st Qu.: 84.5 1st Qu.: 46.0
Mode :character Median :100.0 Median : 83.5
Mean :103.4 Mean :117.0
3rd Qu.:122.0 3rd Qu.:167.2
Max. :213.0 Max. :358.0 The correlation between CDI and PDI is: 0.009Session