Correlation - the basics (R):
The relationship between two randow variables (yi,1 and y1,2) can be described by their destribution. What does the destribution look like?

The distribution of the two random variables yi,1 and y1,2 can be visualized with a correlation matrix, which consists of the pairwise correlations of each variable. This matrix provides a graphical representation of the relationship between the variables, showing how one variable's value tends to change with changes in the other variable's value. Typically, a correlation matrix has values ranging from -1.00 to +1.00, with higher values indicating a stronger positive correlation between the variables and lower values indicating a stronger negative correlation. The closer the correlation coefficient is to 1.00 or -1.00, the stronger the linear relationship between the variables. A correlation of 0 indicates no linear relationship between the variables. Additionally, this correlation matrix can be used to assess the degree of association between two variables, helping to determine if changes in one variable result in predictable changes in the other.