An example Analysis of bivariate normal Distribution and Bivariate correlation Analysis in R language

Through the example analysis of bivariate normal distribution and bivariate correlation analysis in R language, it is believed that many inexperienced people are at a loss about this. Therefore, this paper summarizes the causes and solutions of the problem. Through this article, I hope you can solve this problem.

Pearson coefficient, Spelman coefficient and Kendall coefficient are the three major correlation coefficients that we often use in bivariate correlation analysis. When Pearson coefficient is used, there is a basic condition that the two variables should satisfy the bivariate normal distribution, otherwise it is recommended to choose Spelman correlation coefficient.

Therefore, before the correlation analysis of two continuous data, it is necessary to test the multivariate (binary) normal distribution. In R language, we can do this using the mshapiro.test function in the mvnormtest package.

Case data: employee data

Our backend replied to [employee] to download case data.

Bivariate normal distribution test

Now I want to examine the correlation between the initial salary and the current salary, first of all, let's do the binary normal distribution test.

Mydata