best choice for $N_{b}$ is through the statistical significance value, which is a way to discriminate the measurement with the best signal to noise ratio. In the following analyses we show that the largest statistical significance is obtained with $N_{b}=29$, as summarized in table \[table1\].

The 2PACF: the error bars calculation and the statistical significance {#errors}
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Given the DR12Q sample, in the redshift range $z = 2.20 - 2.25$ and mean redshift $\overline{z}=2.225$, we use the LS estimator given by equation (\[eq2\]), to obtain the 2PACF, $\omega(\theta)$, as displayed in figure \[fig1\]. The calculation of the data points $\omega(\theta)$, represented as dots in the plots of figure \[fig1\], and their error bars are as follows.

Consider that we have $N$ random catalogues, each one sharing the same features as the data sample, that is, it contains the same number of objects and geometry of the data survey. Assume also that we perform this calculation considering $N_b$ bins. Using equation (\[eq2\]), we calculate $N$ times the 2PACF, $\{ \omega^j(\theta) \},$ with $j=1, \cdots, N$, one for each random catalogue. Then, the 2PACF is achieved, for each bin $k$, with $k=1, \cdots, N_b$, from the arithmetic mean: $\omega(\theta_{k}) = (1/N) \, 