Data Analysis > Correlation and Regression > Correlation coefficients and their tests for multiple variables

Combination of correlation coefficients and their tests

If we need to combine correlation and it’s test for hpand mpg in a plot then we can use the ggscatterstats() function from the {ggstatsplot} package.

// install.packages("ggstatsplot")

library(ggstatsplot)

## plot with statistical results

ggscatterstats(data = mtcars, x = hp, y = mpg,

  bf.message = FALSE, marginal = FALSE # remove histograms)

 

Correlation Matrix:

Our dataset “mtcars” contains the following variables:

"mpg"  "cyl"  "disp" "hp"   "drat" "wt"  "qsec" "vs"   "am"   "gear" "carb"

 

Scatterplots for Several pairs of Variables:

Correlation between pairs of variables can be visualized using scatterplot.

If we want to visualize the relationship for several pairs of variables:

    pairs(mtcars[, c("mpg", "disp","hp","drat")])

We can compute correlation of all pairs of variables:

   round(cor(mtcars),digits = 2 )

 

Another readable way to calculate correlation as:

install.packages("corrplot")

library(corrplot)

corrplot(cor(mtcars), method = "number", type = "upper" )

 

 

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