## STATISTICAL GRAPH

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.

**See the methodology of the statistical abstract for more details**

## 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 *and GTCEL) 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.

It is curious the different behaviour between variables **T1** y **T4** of the children and **WB** variable of the children. No doubt it must be that their origin is not the same type of intellengece test.

Another curiosity is that this different behaviour only occurs with arrangement criterions **M** y **2F2M** but not with **F**

IF these results were confirmed, it would appear there are some different functions between masculine and femenine intelligence.

The general multidimensional correlation index (**ICMG**) is 7,55 which is significantly lower than other arrangement criterions. Also, it is smaller with original variables than centred variables.

Likewise, the highest determination coefficient **r²** of this graph is 0,61 which is one of the lowest of The EDI Study, as all the graphs of this statistical research.