KFU. Card publication. Student's t-table modification for the linear correlation coefficients estimation in the small samples cases

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FEDERAL UNIVERSITY

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STUDENT'S T-TABLE MODIFICATION FOR THE LINEAR CORRELATION COEFFICIENTS ESTIMATION IN THE SMALL SAMPLES CASES

Form of presentation

Articles in international journals and collections

Year of publication

2022

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Authors, employees of KFU

Akhmetova Irina Anatolevna, author

Voroncov Dmitriy Petrovich, author

Shikhalyov Anatoliy Mikhaylovich, author

Other authors

Verzun Natalya , author

Kolbanev Mikhail , author

Authors, students KFU

Igushkin Ilya Arnoldovich, author

Bibliographic description in the original language

Student's t-table modification for the linear correlation coefficients estimation in the small samples cases. Ilya Igushkin, Anatoly Shikhalev, Dmitry Vorontsov, Natalya Verzun, Mikhail Kolbanyov, Irina Akhmetova. Proceedings of VIII International Conference on Information Technology and Nanotechnology (ITNT-2022), 23-27.05.2022, DOI:10.1109/ITNT55410.2022.9848663

Annotation

C�� VIII �� «�� » (��-2022)

Keywords

distribution law, correlation coefficient, Chaddock?s scale, turbulent economy, Student's t-test table, statistical population, consent criteria

The name of the journal

C�� VIII �� «�� » (��-2022)

URL

https://ieeexplore.ieee.org/document/9848663

Please use this ID to quote from or refer to the card

https://repository.kpfu.ru/eng/?p_id=267030&p_lang=2

Full metadata record

Field DC	Value	Language
dc.contributor.author	Akhmetova Irina Anatolevna	ru_RU
dc.contributor.author	Voroncov Dmitriy Petrovich	ru_RU
dc.contributor.author	Shikhalyov Anatoliy Mikhaylovich	ru_RU
dc.contributor.author	Verzun Natalya	ru_RU
dc.contributor.author	Kolbanev Mikhail	ru_RU
dc.contributor.author	Igushkin Ilya Arnoldovich	ru_RU
dc.date.accessioned	2022-01-01T00:00:00Z	ru_RU
dc.date.available	2022-01-01T00:00:00Z	ru_RU
dc.date.issued	2022	ru_RU
dc.identifier.citation	Student's t-table modification for the linear correlation coefficients estimation in the small samples cases. Ilya Igushkin, Anatoly Shikhalev, Dmitry Vorontsov, Natalya Verzun, Mikhail Kolbanyov, Irina Akhmetova. Proceedings of VIII International Conference on Information Technology and Nanotechnology (ITNT-2022), 23-27.05.2022, DOI:10.1109/ITNT55410.2022.9848663	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=267030&p_lang=2	ru_RU
dc.description.abstract	C�� VIII �� «�� » (��-2022)	ru_RU
dc.description.abstract	In the linear correlation coefficient calculations for the statistical significance estimation is often used the famous Chaddock's scale of the relationship between the studied phenomena with the characteristics like “weak”, “medium”, “visible”, “high”, “very high”, and for the significance evaluation used the Student's t-test table with the fixed alpha-level (α = 0.10; 0.05; 0.01) and with the available degrees of freedom. If the calculated values of the linear correlation coefficient are less than critical, then as usual the researchers will increase the number of initial observations N. However, in an unstable economics period this is not always possible. Therefore, we have the task of estimating the confidence interval for the calculated value of the linear correlation coefficient, especially to its lower bound (of confidence level): what if the calculated module of linear correlation coefficient will be met the reliability requirements according to the famous t-Student criterion? Moreover, this means that the significance in (both) cases is assessed on a step by step manner which is not fully expedient. For the decision of this problem we propose to use the modified Student's scale and then it is also possible to use the Chaddock's scale. As the raw data we use statistical aggregates with the limited size; after some modifications we create on this variation series and apply the consent criteria. For the noted problem solving we also must note the received equations for LCC error and non-strict inequality. Some part of the results was obtained with the program made in FoxPro 2.5 which was created by the member of the author's team (Anatoly Shikhalev).	ru_RU
dc.language.iso	ru	ru_RU
dc.subject	distribution law	ru_RU
dc.subject	correlation coefficient	ru_RU
dc.subject	Chaddock?s scale	ru_RU
dc.subject	turbulent economy	ru_RU
dc.subject	Student's t-test table	ru_RU
dc.subject	statistical population	ru_RU
dc.subject	consent criteria	ru_RU
dc.title	Student's t-table modification for the linear correlation coefficients estimation in the small samples cases	ru_RU
dc.type	Articles in international journals and collections	ru_RU