﻿ Statistical research on IQ, the EDI study
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# Statistical research on IQ

The EDI study on evolutionary psychology, the methodology of the statistical study, and IQ statistical correlations among intelligence test variables of families.

## STATISTICAL ABSTRACT METHODOLOGY OF THE STATISTICAL STUDY

The title of each graph of the statistical study indicates the parents' variables (R or M & F) to which the correlations relate. Each point of the colored lines represents the correlations with the observational C variables of the 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, appear on the left-hand side of the graph. The criteria order of the groups of 1 to 10 values located on the right-hand side is the variable mentioned at the bottom of the graph.

Each graph condenses more than 5,000 different points of information for the interrelations between:

• 70 values of each IQ variable of the fathers, mothers, and children
• 8 variables of the IQ of fathers, mothers, and children
• 3 variables of individual averages of the previous variables
• 10 criteria of value arrangement
• 10 sizes of groupings of individuals
• 20 values of evolution’s parameters in a sensitivity analysis
• Countless random variables created in the simulation model

The set of graphs collects all these interrelations, that is, more than 1,000,000 values. Note that the average of any two values has a dynamic that is independent of the two values.

An example of the data source could be having a historical sample of 70 packets of cigarettes. However, the sample can be of 70 elements, or many more if, for each packet, the analysis would consider the following aspects:

• The number of cigarettes per packet
• The size of the cigarettes
• The type of cardboard the packet has
• The color
• If it has any images
• If it has any health warnings
• The type or severity of these warnings
• Information about the level of nicotine and tar

The graphs show a instantaneous perception of the goodness-of-fit of a specification; they represent sixty coefficients of determination (r²) that highlights the underlying relations of the involved data.

In order to facilitate the comparative analysis, there is a multidimensional correlation index (from now on MCI) to represent with one number the global precision of the adjustments shown in any graph. It will be the sum of the determination coefficients of the ten rearranged variables.

There will be an MCI for each variable and a Global MCI for the three variables studied in each graph. The maximum GMCI will be 30 since the graphs always contain three variables and ten groupings.

On the right-hand side and below the variable, there are the r² and the GMCI to help to understand the correlations involved.

The results are surprising, which can be observed both in the graphs of the statistical annex and in the following tables. An aspect that will allow reaching some crucial conclusions is the model sensitivity of the arrangement criterion.

Go to The EDI Study

Go to The EDI Study

Go to The EDI Study

Go to The EDI Study

Go to The EDI Study

q053 Back to family study

q058 Go to The EDI Study

Go to The EDI Study

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