the *observed* not-zero correlation coefficients if the *actual* correlation coefficient were, in fact, zero ($p-$value), is less than $10^{-5}$. Therefore, the following three correlations have strong statistical significance:

-   The wind resource IAV and the long-term windiness correction uncertainties are moderately correlated ($R = 0.49$, $p = 1.9 \cdot 10^{-29}$).

-   The linear regression and reference wind speed data uncertainties are weakly correlated ($R = 0.35$, $p = 2.5 \cdot 10^{-15}$).

-   The wind resource IAV and the linear regression uncertainties appear weakly negatively correlated ($R = -0.21$, $p = 2.6 \cdot 10^{-6}$).

The first correlation noted earlier (wind resource IAV and long-term windiness correction) is explained simply by the fact that both uncertainty components are driven by wind resource variability. At a site with large wind variability, IAV will be large by definition and so will the uncertainty introduced by different lengths of time series used for the long-term AEP calculation.\
The correlation between linear regression and reference wind speed data uncertainties can be justified given the dependence of both these uncertainty components on the number of data points used in the regression between energy production data and concurrent wind speed data (Figure \[regression\_uncertainty\]).

![image](f07){width="16cm"}

Both the slope and 