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Performing F-Test in R programming – var.test() Method

  • Last Updated : 10 May, 2020

With the help of var.test() method, we can perform the f-test between two normal population with some hypothesis that variances of two populations are equal in R programming.

Syntax: var.test()

Return: Returns the F-Test score for some hypothesis.

Example 1:




x <- rnorm(50, mean=0)
y <- rnorm(50, mean=1)
  
# Using var.test() method
  
gfg <- var.test(x, y)
  
print(gfg)

Output:

F test to compare two variances

data:  x and y
F = 1.0779, num df = 49, denom df = 49, p-value = 0.794
alternative hypothesis: true ratio of variances is not equal to 1
95 percent confidence interval:
 0.6116778 1.8994484
sample estimates:
ratio of variances 
          1.077892 

Example 2:




x <- rnorm(50, mean=1.2)
y <- rnorm(50, mean=1.8)
  
# Using var.test() method
  
gfg <- var.test(x, y)
  
print(gfg)

Output:

F test to compare two variances

data:  x and y
F = 2.382, num df = 49, denom df = 49, p-value = 0.002911
alternative hypothesis: true ratio of variances is not equal to 1
95 percent confidence interval:
 1.351715 4.197491
sample estimates:
ratio of variances 
          2.381976 

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