To find the P-value of correlation coefficient in R, you can use **cor.test()** function in R.

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

**Method 1: Use cor.test() Function**

```
cor.test(df$column1,df$column2)
```

The following example shows how to find P-value of correlation coefficient in R using **cor.test()** function.

## Using cor.test() Function

Let’s see how we can use **cor.test()** function in R:

```
# Create data frame
df <- data.frame(Pressure1=c(78.2, 88.2, 71.7, 80.21, 84.21, 82.56, 72.12, 73.85),
Temperature=c(35, 36, 37, 38, 32, 30, 31, 34),
Pressure2=c(12, 13, 11, 12, 14, 15, 13, 15))
# Calculate correlation coefficient and p-value
c <- cor.test(df$Pressure1,df$Pressure2)
# Display correlation coefficient and p-value
print(c)
```

Output:

```
Pearson's product-moment correlation
data: df$Pressure1 and df$Pressure2
t = 0.67598, df = 6, p-value = 0.5242
alternative hypothesis: true correlation is not equal to 0
95 percent confidence interval:
-0.5398497 0.8174562
sample estimates:
cor
0.266023
```

Here from output we can say correlation coefficient is 0.266023 and p-value is 0.5242 between **Pressure1** and **Pressure2** column of dataframe.