This chart tells us that variation for any individual set of results can be quite

[zihadhasan019]

The page with the most links is assigned "1," the second-most links gets "2," etc). The smoothness of the line suggests it is fairly accurate, but we can be precise about our accuracy. The error bars below show the 95th percentile confidence interval for estimates of the mean. We're looking good. The correlation is quite strong, suggesting that yes, the number of external, followed links is important and the standard error is low, so we can feel confident that the correlation is real.


Clearly, though, comparing with the perfect fit lin email lists australia e, links are not the whole picture. Having the most links out of your peers in the results is likely a very good goal, but it can't be the only goal. The last piece here is to examine the standard deviation. This can tell us how much an individual page might vary from the averages. large, so getting more links isn't always going to be a clear win.





It's notable that in this chart, standard deviation here is shown for the 95th percentile confidence, which is actually 1.97 standard deviations away from the mean. On the whole, # of external, followed links is clearly important and well correlated, but we're going to need to get more advanced in our models and broader in our thinking to get actionable information at a granular level. Can Any Single Metric Predict the Rankings? Boy, that sure would be nice.