Given X data frame that consists of 6 objects., each with 2 attributes (layout as a table):

	X1	X2
1	19	12
2	22	6
3	6	9
4	3	15
5	2	13
6	20	5

-convert data frame into centered matrix;

-Compute Covariane matrix C_x (with estimated sample mean version);

-compute characteristic polynomial and eigenvalues of C_x ;

-find principal components/rotation matrix;

-how much varience (%) is explained by new first principal component y₁;

-compute PCA transformation matrix (rotation) of X (without centering).