The title of each graph of the statistical study indicates the parents variables (R or M & F) to which the correlations are related. These correlations are represented by each point of the coloured lines corresponding to each examined C variable (children).
Likewise, the variables of unknown order, formed by the different groups of 1 to 10 values from the 70 IQ values of each parent and children variables are placed on the left hand side of the graph. The groups of 1 to 10 values located on the right hand side have been previously ordered with the variable mentioned at the bottom of the graph.
Indeed, an almost instantaneous perception of the exactitude of the particular specification of the statistical study is obtained; sixty coefficients of determination (r²) are shown in a way that highlights the global and underlying relations of the involved data set.
QUANTITATIVE RESEARCH COMMENTS
1. General statistical significance
The great increase of the correlation for the estimation of homogenous groups cannot be imputed to the reduction of 68 to 5 or 4 degrees of freedom, since the estimation with non-homogenous groups, without previous rearrangement, has the same degrees of freedom and the correlation even lowers with respect to the sample without grouping.
When the model of the statistical study has more freedom with the two intelligence quotients' variables, M and F, either it definitely adjusts better by statistical effect or the statistical data set we have available is a particular case.
In general, the model of genetic evolution of intelligence (Mendelian genetics – Conditional intelligence – Gobal Cognitive Theory) adjusts perfectly, showing an r² superior to 0.9 in several cases. Bearing in mind the tendency to increase the goodness of fit with the size of rearranged groups, we could asume it would be over 0,9 in almost all the cases for groups bigger than 20, of course, it should be needed a bigger sample.
2. Quantitative research with the Social Model and a special rearrangement criterion to check the Genetic Information Verification method (GIV).
The main goal of this quantitative research is not to verify the genetic nature of intelligence but to demonstrate the operational existence of the Genetic Information Verification method (GIV) pointed out by the GTCEL (General Theory of the Conditional Evolution of Life) for the intelligence particular case; inasmuch as the determination of the criteria to identify the significant gene or, more explicitly, the logical genetic mechanisms of the intellectual potential generation.
In the statistical graphs of the Social Model we have seen that the criterion of arrangement based on *M1F1 is very good, confirming the behaviour predictions derived from the presence of the GIV method.
If the Genetic Information Verification method (GIV) method is present, the C variables of the children are configured with the *M1F1 component with a 50% probability.
In general, the objective function R is almost as good as M&F; therefore, its definition contains the true rules of the transmission of human intelligence.
From another point of view, function *R is also very good as arrangement criterion. It makes sense because it incorporates the effect of the genetic combination in agreement with the genetic laws of Mendel. In despite of this, it is a bit inferior to the *M1F1 arrangement criterion.
In order to be sure of the behaviour foreseen by the GIV method, we are going to use a special rearrangement criterion: the opposed order of *M1F1, that is to say, the order of the vector formed by the grater values of M2 and F2, that we will call *2F2M.
The result is substantially poorer with * 2F2M than with the *M1F1; therefore, we may assume more rigorously that the GIV method, or something similar, is operative in the genetic characters associated to intelligence. It is similar to the concept of recessive genes but not the same; even more, I am using genes as genetic information in general.
Likewise, it seems that the main functions of intelligence, or those evolving faster, are fairly concentrated in only one chromosome.
The precision of the results is really important if we want our interpretations to maintain a certain degree of confidence; when the lines corresponding to C variables of the children and their different groupings follow a clear tendency we can assume that the results are not consequence of statistical coincidences. This fact is especially visible within the analysis of variables X3 and X6.
For the same reason, we have included another two rearrangement criteria in the analysis of the centred variables, that is to say, mother’s variable M and father’s variable F.
For these two vectors of the progenitors, the result is superior compared to that obtained with variable * 2F2M, but it continues being quite inferior in respect to *M1F1.
3. Statistical significant figures of this particular graph of the quantitative research.
As you can clearly see by its form, the three dependent variables of the children, analyzed in the model, behave in a very similar way to the progenitors' explanatory variables M & F
The general multidimensional correlation index (ICMG) is 12,39 which is significantly lower than other arrangement criterions. However, it is bigger with centred variables than original variables.
Likewise, the highest determination coefficient r² of this graph is 0,70 which is one of the lowest of The EDI Study, as all the graphs of this statistical research.