What is the difference in meaning between the Pearson Coefficient and the error from a least squares regression line?

From what I understand, the Pearson Coefficient determines if there is a linear relationship between some data. However, doesn't the error from a least squares regression line also do basically the same thing?

I have some points that have around r~=0.90 with error~=15. I also have some other points around r~=0.85 with error~=45. Is there a big difference in meaning between the two? Why is the error rate 3x for only a 0.05 difference in the Pearson Coefficient?

I suppose you are talking about a univariate linear regression (right?). In a univariate linear regression $$y=a+bx+e$$ the correlation between y and x is the square root of the $$R^2$$ of the regression (i.e. the percentage of the total sum of squares of the dependent variable which is explained by the model, or, if you prefer, the complement to 1 of the percentage explained by the residuals). For more help check this