explain.pearson: Pearson Correlation Function Explained

In LearningRlab: Statistical Learning Functions

Pearson Correlation Function Explained

Description

Step by step demonstration of the pearson correlation calculus.

Usage

explain.pearson(x,y)

Arguments

x	Should be a vector
y	Should be a vector

Details

To calculate the pearson correlation, the user should give two vectors of numbers. The result is the covariance of the two vectors of numbers divided by the product of their standard deviations. We can saw the pearson correlation formule in the pearson_ help document.

Value

Numeric result and the process of this calculus explained.

Note

A vector is created by c(), like c(1,2,3,4,5) creates a vector with the numbers: 1,2,3,4,5

Author(s)

Jose Manuel Gomez Caceres, [e-mail]
Juan Jose Cuadrado, [e-mail]
Universidad de Alcala de Henares

Examples

  
  #data creation
  data <- c(10,4,5,7,3,4,1)
  data2 <- c(1,8,3,4,4,5,7)
  
  explain.pearson(data, data2)
    

LearningRlab documentation built on Aug. 31, 2023, 1:08 a.m.