To calculate correlation between multiple variables in R, you can use cor() function. This function computes the correlation coefficient between variables in a data frame or matrix.

The following method shows how you can do it with syntax.

Method: Use cor() Function

cor(x,y)


The following examples shows how to use cor() function in R.

## Use cor() Function to Calculate Correlation Between Two Variables

Let’s see how we can use cor() function to calculate correlation between two variables of data frame:

# Create data frame
df <- data.frame(Pressure1=c(78.2, 88.2, 71.7, 80.21, 84.21, 82.56, 72.12, 73.85),
Pressure2=c(12, 13, 11, 12, 14, 15, 13, 15),
Temperature=c(35, 36, 37, 38, 32, 30, 31, 34))

# Calculate correlation
c <- cor(df$Pressure1,df$Pressure2)

# Print correlation
print(c)


Output:

[1] 0.266023


As the output shows 0.266023 correlation between Pressure1 and Pressure2 columns of data frame.

## Use cor() Function to Calculate Correlation for Entire Data Frame

Let’s see how we can use cor() function for entire data frame:

# Create data frame
df <- data.frame(Pressure1=c(78.2, 88.2, 71.7, 80.21, 84.21, 82.56, 72.12, 73.85),
Pressure2=c(12, 13, 11, 12, 14, 15, 13, 15),
Pressure3=c(25, 28, 29, 30, 32, 27, 29, 21),
Temperature=c(35, 36, 37, 38, 32, 30, 31, 34))

# Calculate correlation matrix
c <- cor(df)

# Print correlation matrix
print(c)


Output:

Pressure1  Pressure2  Pressure3 Temperature
Pressure1    1.00000000  0.2660230  0.3064410 -0.02750833
Pressure2    0.26602303  1.0000000 -0.3662667 -0.71384311
Pressure3    0.30644101 -0.3662667  1.0000000  0.02005080
Temperature -0.02750833 -0.7138431  0.0200508  1.00000000


Here the output shows correlation between all columns of data frame.