Table 2. Summary of out-degree scaling analysis.
Colony | Slope1 | SE | R squared | P-value |
1 | −2.302233 | 0.2453528 | 0.9362024 | 0.0001 |
2 | −1.495037 | 0.4009239 | 0.7766024 | 0.0203 |
3 | −1.993387 | 0.397453 | 0.80741 | 0.0024 |
4 | −2.076154 | 0.1107807 | 0.9859641 | 0 |
5 | −1.718984 | 0.3488862 | 0.8585369 | 0.0079 |
6 | −2.129866 | 0.2474018 | 0.9251065 | 0.0001 |
7 | −1.93115 | 0.2274315 | 0.9231746 | 0.0001 |
8 | −2.371344 | 0.3693494 | 0.8918231 | 0.0014 |
9 | −2.230362 | 0.3129172 | 0.8788996 | 0.0002 |
10 | −2.343456 | 0.3201249 | 0.9146595 | 0.0007 |
11 | −1.773185 | 0.4323595 | 0.7061254 | 0.0046 |
12 | −2.045588 | 0.2359468 | 0.8930656 | 0 |
(1) This is the OLS-estimated slope for the relationship describing how the number of nodes with a given number of out-degree edges scales with out-degree. The data (x) were transformed prior to regression according to log10(x+1). The absolute value of the slope is an estimate for the degree distribution power law exponent (alpha).