How this chapter is organized?

Correlation Test Between Two Variables in R

Brief outline:

• What is correlation test?
• Methods for correlation analyses
• Correlation formula
  • Pearson correlation formula
  • Spearman correlation formula
  • Kendall correlation formula
• Compute correlation in R
  • R functions
  • Import your data into R
  • Visualize your data using scatter plots
  • Preliminary test to check the test assumptions
  • Pearson correlation test
  • Kendall rank correlation test
  • Spearman rank correlation coefficient
• Interpret correlation coefficient

Read more: —>Correlation Test Between Two Variables in R.

Correlation Matrix: Analyze, Format and Visualize

Correlation matrix is used to analyze the correlation between multiple variables at the same time.

Brief outline:

• What is correlation matrix?
• Compute correlation matrix in R
  • R functions
  • Compute correlation matrix
  • Correlation matrix with significance levels (p-value)
  • A simple function to format the correlation matrix
  • Visualize correlation matrix
    • Use symnum() function: Symbolic number coding
    • Use corrplot() function: Draw a correlogram
    • Use chart.Correlation(): Draw scatter plots
    • Use heatmap()

scatter plot, chart

Read more: —>Correlation Matrix: Analyze, Format and Visualize.

Visualize Correlation Matrix using Correlogram

Correlogram is a graph of correlation matrix. Useful to highlight the most correlated variables in a data table. In this plot, correlation coefficients are colored according to the value. Correlation matrix can be also reordered according to the degree of association between variables.

Brief outline:

• Install R corrplot package
• Data for correlation analysis
• Computing correlation matrix
• Correlogram : Visualizing the correlation matrix
  • Visualization methods
  • Types of correlogram layout
  • Reordering the correlation matrix
  • Changing the color of the correlogram
  • Changing the color and the rotation of text labels
  • Combining correlogram with the significance test
  • Customize the correlogram

library(corrplot)
library(RColorBrewer)
M <-cor(mtcars)
corrplot(M, type="upper", order="hclust",
         col=brewer.pal(n=8, name="RdYlBu"))

Read more: —>Visualize Correlation Matrix using Correlogram.

Elegant Correlation Table using xtable R Package

The aim of this article is to show you how to get the lower and the upper triangular part of a correlation matrix. We will use also xtable R package to display a nice correlation table.

Brief outline:

• Correlation matrix analysis
• Lower and upper triangular part of a correlation matrix
• Use xtable R package to display nice correlation table in html format
• Combine matrix of correlation coefficients and significance levels

Read more: —>Elegant correlation table using xtable R package.

Correlation Matrix : An R Function to Do All You Need

The goal of this article is to provide you a custom R function, named rquery.cormat(), for calculating and visualizing easily a correlation matrix in a single line R code.

Brief outline:

• Computing the correlation matrix using rquery.cormat()
  • Upper triangle of the correlation matrix
  • Full correlation matrix
  • Change the colors of the correlogram
  • Draw a heatmap
• Format the correlation table
• Description of rquery.cormat() function

source("http://www.sthda.com/upload/rquery_cormat.r")
mydata <- mtcars[, c(1,3,4,5,6,7)]
require("corrplot")
rquery.cormat(mydata)

$r
        hp  disp    wt  qsec  mpg drat
hp       1                            
disp  0.79     1                      
wt    0.66  0.89     1                
qsec -0.71 -0.43 -0.17     1          
mpg  -0.78 -0.85 -0.87  0.42    1     
drat -0.45 -0.71 -0.71 0.091 0.68    1

$p
          hp    disp      wt  qsec     mpg drat
hp         0                                   
disp 7.1e-08       0                           
wt   4.1e-05 1.2e-11       0                   
qsec 5.8e-06   0.013    0.34     0             
mpg  1.8e-07 9.4e-10 1.3e-10 0.017       0     
drat    0.01 5.3e-06 4.8e-06  0.62 1.8e-05    0

$sym
     hp disp wt qsec mpg drat
hp   1                       
disp ,  1                    
wt   ,  +    1               
qsec ,  .       1            
mpg  ,  +    +  .    1       
drat .  ,    ,       ,   1   
attr(,"legend")
[1] 0 ' ' 0.3 '.' 0.6 ',' 0.8 '+' 0.9 '*' 0.95 'B' 1

Read more: —>Correlation Matrix : An R Function to Do All You Need.

See also

• R Basics
• Import and Export Data using R
• Preparing and Reshaping Data in R for Easier Analyses
• Data Manipulation in R
• Data visualization
• Descriptive Statistics and Graphics

Infos

This analysis has been performed using R statistical software (ver. 3.2.4).