Strong reciprocal dependencies as exceptions when correlations are weak
The article discusses examples of strong (SV > 0.7) simplest nonlinear dependencies in a problem for 114 indicators of 9 psychodiagnostic techniques, which represent exceptions in the context of many specific problems for studying statistical relationships, when two reciprocal dependencies, Y...
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| Format: | Article |
| Language: | English |
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Publishing House of the State University of Management
2024-06-01
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| Series: | Вестник университета |
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| Online Access: | https://vestnik.guu.ru/jour/article/view/5284 |
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| author | M. M. Basimov |
| author_facet | M. M. Basimov |
| author_sort | M. M. Basimov |
| collection | DOAJ |
| description | The article discusses examples of strong (SV > 0.7) simplest nonlinear dependencies in a problem for 114 indicators of 9 psychodiagnostic techniques, which represent exceptions in the context of many specific problems for studying statistical relationships, when two reciprocal dependencies, Y(X) and X(Y), are strong. There were only four such dependencies in the model for quintas of the independent variable within the framework of very weak and weak correlations (a total of 180 strong simplest nonlinear dependencies). The author quantitatively analysed and qualitatively interpreted the dependencies for three pairs of variables: “16PF-E: Submissive – Assertive” of R.B. Cattell’s questionnaire and “Competition” of K.W. Thomas’s methodology (SV = 0.78 and SV’ = 0.72 at r = 0.15); “16PF-Q3: Low self-control – High self-control” and “16PF-L: Trusting – Suspicious” of R.B. Cattell’s questionnaire (SV = 1.17 and SV’ = 0.91 at r = 0.28); “Psychasthenia” of the Minnesota Multiphasic Personality Inventory and “Suspicious type” of T.F. Leary’s methodology (SV = 0.84 and SV’ = 0.73 at r = 0.19). For the pair of variables “Low self-control – High self-control” and “Trusting – Suspicious”, models of linear regression are also considered. It is built on the basis of a dependence that is far from linear, as shown by Pearson’s coefficient of weak correlation equal to 0.28. At the same time, founded on the rule for interpreting the absolute value of the correlation coefficient for a sample of 120 subjects (widely used in the psychological community), it indicates the significance of the relationship at the p = 0.01 level, which inevitably requires a linear interpretation. For clarity, the information discussed in the article is illustrated by graphical representations of the dependencies under consideration. |
| format | Article |
| id | doaj-art-5dc1bc3471bb4d148d08cfac732ceb57 |
| institution | Kabale University |
| issn | 1816-4277 2686-8415 |
| language | English |
| publishDate | 2024-06-01 |
| publisher | Publishing House of the State University of Management |
| record_format | Article |
| series | Вестник университета |
| spelling | doaj-art-5dc1bc3471bb4d148d08cfac732ceb572025-02-04T08:28:21ZengPublishing House of the State University of ManagementВестник университета1816-42772686-84152024-06-010523324510.26425/1816-4277-2024-5-233-2453117Strong reciprocal dependencies as exceptions when correlations are weakM. M. Basimov0Institute of World CivilizationsThe article discusses examples of strong (SV > 0.7) simplest nonlinear dependencies in a problem for 114 indicators of 9 psychodiagnostic techniques, which represent exceptions in the context of many specific problems for studying statistical relationships, when two reciprocal dependencies, Y(X) and X(Y), are strong. There were only four such dependencies in the model for quintas of the independent variable within the framework of very weak and weak correlations (a total of 180 strong simplest nonlinear dependencies). The author quantitatively analysed and qualitatively interpreted the dependencies for three pairs of variables: “16PF-E: Submissive – Assertive” of R.B. Cattell’s questionnaire and “Competition” of K.W. Thomas’s methodology (SV = 0.78 and SV’ = 0.72 at r = 0.15); “16PF-Q3: Low self-control – High self-control” and “16PF-L: Trusting – Suspicious” of R.B. Cattell’s questionnaire (SV = 1.17 and SV’ = 0.91 at r = 0.28); “Psychasthenia” of the Minnesota Multiphasic Personality Inventory and “Suspicious type” of T.F. Leary’s methodology (SV = 0.84 and SV’ = 0.73 at r = 0.19). For the pair of variables “Low self-control – High self-control” and “Trusting – Suspicious”, models of linear regression are also considered. It is built on the basis of a dependence that is far from linear, as shown by Pearson’s coefficient of weak correlation equal to 0.28. At the same time, founded on the rule for interpreting the absolute value of the correlation coefficient for a sample of 120 subjects (widely used in the psychological community), it indicates the significance of the relationship at the p = 0.01 level, which inevitably requires a linear interpretation. For clarity, the information discussed in the article is illustrated by graphical representations of the dependencies under consideration.https://vestnik.guu.ru/jour/article/view/5284linear statistical dependencenonlinear statistical dependencecoefficient of correlationsignificant correlationcoefficient of connection strengthcomparative weightinesslinear regressioninterpretations |
| spellingShingle | M. M. Basimov Strong reciprocal dependencies as exceptions when correlations are weak Вестник университета linear statistical dependence nonlinear statistical dependence coefficient of correlation significant correlation coefficient of connection strength comparative weightiness linear regression interpretations |
| title | Strong reciprocal dependencies as exceptions when correlations are weak |
| title_full | Strong reciprocal dependencies as exceptions when correlations are weak |
| title_fullStr | Strong reciprocal dependencies as exceptions when correlations are weak |
| title_full_unstemmed | Strong reciprocal dependencies as exceptions when correlations are weak |
| title_short | Strong reciprocal dependencies as exceptions when correlations are weak |
| title_sort | strong reciprocal dependencies as exceptions when correlations are weak |
| topic | linear statistical dependence nonlinear statistical dependence coefficient of correlation significant correlation coefficient of connection strength comparative weightiness linear regression interpretations |
| url | https://vestnik.guu.ru/jour/article/view/5284 |
| work_keys_str_mv | AT mmbasimov strongreciprocaldependenciesasexceptionswhencorrelationsareweak |