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rcorrelationpearson-correlation

How to interpret correlation coefficient

I am trying to find the correlation coefficient in R between my dependent and independent variable.

data("mtcars")
my_data <- mtcars[, c(1,3,4,5,6,7)]
res <- cor(my_data)
round(res, 2)

As a result, I got a correlation matrix, some with +ve or -ve.

For ex: if correlation coefficient between mpg and disp is -0.85, how can I know which variable is decreasing and the one increasing?

Solution

  • Consider the following script, which just compares mpg and disp:

    res1 <- cor(mtcars$mpg,  mtcars$disp)
res2 <- cor(mtcars$disp, mtcars$mpg)
round(res1, 2)
round(res2, 2)

    The output from both calls is -0.85. In other words, the nature of the correlation coefficient is not about the order of one variable against the other. Rather, a negative correlation coefficient means that as mpg increases, disp tends to decrease. And we could also phrase this by saying that as disp increases, mpg tends to decrease.