Dear all,
I am conducting a principal component analysis of metal elements in the soils of Bundala National park. But Pottasium was strongly negatively loaded. How can I discuss it? What is the reason for that?
Dear Mahesh,
If you are using PCA, it means that you are processing a given matrix with n rows (observations) and p columns (variables).
PCA tries to split your original data in several k new variables (k
Each resulting component is a linear combniation of the columns you have. The signs should be interpreted "as if" each linear combination was a regression line. Also keep an eye on the explained variance by each component.
Dear Mahesh Galappaththi,
First of all you need to understand what the loading is before the sign (positive or negative). Loadings in Principal Component Analysis (PCA) tells you how much each or particular variable contributes to a particular principal component (PC) either PC1 or PC2. Large PCA loadings either negative or positive indicates that a particular variable has a strong relationship to a particular PC. Positive loadings tells you that a variable and a PC are positively correlated (An increase in one result is an increase in the other). Negative loadings simply indicates a negative correlation. Large loadings either positive or negative indicate that a particular variable has a strong effect on that PC.
I hope you are OK with the explanation.
Best regds.
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