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Abdul-Rahman A. Time Series Analysis in Forecasting Mental Addition and Summation Performance. Front Psychol. 2020;11:911doi: 10.3389/fpsyg.2020.00911.
Abdul-Rahman, A. (2020). Time Series Analysis in Forecasting Mental Addition and Summation Performance. Frontiers in psychology, 11911. https://doi.org/10.3389/fpsyg.2020.00911
Abdul-Rahman, Anmar. "Time Series Analysis in Forecasting Mental Addition and Summation Performance." Frontiers in psychology vol. 11 (2020): 911. doi: https://doi.org/10.3389/fpsyg.2020.00911
Abdul-Rahman A. Time Series Analysis in Forecasting Mental Addition and Summation Performance. Front Psychol. 2020 May 20;11:911. doi: 10.3389/fpsyg.2020.00911. eCollection 2020. PMID: 32508718; PMCID: PMC7251292.
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Front Psychol. 2020 May 20;11:911. doi: 10.3389/fpsyg.2020.00911. eCollection 2020.

Time Series Analysis in Forecasting Mental Addition and Summation Performance.

Frontiers in psychology

Anmar Abdul-Rahman

Affiliations

  1. Department of Ophthalmology, Counties Manukau DHB, Auckland, New Zealand.

PMID: 32508718 PMCID: PMC7251292 DOI: 10.3389/fpsyg.2020.00911

Abstract

An ideal performance evaluation metric would be predictive, objective, easy to administer, estimate the variance in performance, and provide a confidence interval for the level of uncertainty. Time series forecasting may provide objective metrics for predictive performance in mental arithmetic. Addition and summation (addition combined with subtraction) using the Japanese Soroban computation system was undertaken over 60 days. The median calculation time in seconds for adding 10 sequential six digit numbers [CT

Copyright © 2020 Abdul-Rahman.

Keywords: ARIMA model; cognitive performance; forecasting–methodology; mathematics; time series

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