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It evaluates alternative ARIMA specifications and compares model fit using AIC, BIC/SIC, HQC, and R-squared, highlighting which combinations better explain variation for each group and examination period.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & 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data is compiled in the study?","Question",{"text":63,"@type":64},"The document lists CP ALE results by examination date (May and October), including total passed, total first-timer (or repeater) examinees, and the resulting passing rate percentages.","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"How does the study model forecasting of passing rates?",{"text":68,"@type":64},"It uses ARIMA time-series models and tests multiple ARIMA parameter sets to model the passing rate behavior over time for May and October, separately for first-timers and repeaters.",{"name":70,"@type":61,"acceptedAnswer":71},"Which metrics are used to evaluate the ARIMA models?",{"text":72,"@type":64},"Model performance is compared using Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC)/Schwarz Information Criterion (SIC), Hannan-Quinn Information Criterion (HQC), and the coefficient of determination (R 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Date of\u003Cbr>Examination | Total\u003Cbr>no. of\u003Cbr>Passed | Total no. of\u003Cbr>First-timer\u003Cbr>Examinees | Passing\u003Cbr>rate |\n| MAY 2010 | 739 | 2,065 | 35.79% |\n| MAY 2011 | 820 | 2,245 | 36.53% |\n| MAY 2012 | 988 | 2,512 | 39.33% |\n| MAY 2013 | 765 | 2,534 | 30.19% |\n| *MAY 20141 | 591 | 2,827 | 20.91% |\n| MAY 2015 | 793 | 2,611 | 30.37% |\n| MAY 2016 | 1,191 | 2,926 | 40.70% |\n| MAY 2017 | 1,279 | 3,756 | 34.05% |\n| MAY 2018 | 1,067 | 3,768 | 28.32% |\n| MAY 2019 | 546 | 4,114 | 13.27% |\n| *MAY 20212 | 188 | 1,498 | 12.55% |\n| MAY 2022 | 510 | 2,519 | 20.25% |\n| MAY 2023 | 1,404 | 5,077 | 27.65% |\n\n\n| OCTOBER |  |  |  |\n| --- | --- | --- | --- |\n| Date of\u003Cbr>Examination | Total\u003Cbr>no. of\u003Cbr>Passed | Total no. of\u003Cbr>First-timer\u003Cbr>Examinees | Passing\u003Cbr>rate |\n| OCT 2010 | 3,006 | 5,811 | 51.73% |\n| OCT 2011 | 3,226 | 6,046 | 53.36% |\n| OCT 2012 | 3,883 | 7,320 | 53.05% |\n| OCT 2013 | 3,605 | 7,839 | 45.99% |\n| OCT 2014 | 3,363 | 8,389 | 40.09% |\n| OCT 2015 | 4,397 | 9,734 | 45.17% |\n| OCT 2016 | 4,476 | 10,645 | 42.05% |\n| OCT 2017 | 3,869 | 10,968 | 35.28% |\n| OCT 2018 | 3,115 | 10,682 | 29.16% |\n| OCT 2019 | 1,662 | 10,532 | 15.78% |\n| *OCT 20213 | 128 | 782 | 16.37% |\n| OCT 2022 | 981 | 4,160 | 23.58% |\n| OCT 2023 | 1,551 | 5,052 | 30.70% |\n\n| MAY |  |  |  |\n| --- | --- | --- | --- |\n| Date of\u003Cbr>Examination | Total\u003Cbr>no. of\u003Cbr>Passed | Total no. of\u003Cbr>Repeater\u003Cbr>Examinees | Passing\u003Cbr>rate |\n| MAY 2010 | 1,147 | 2,707 | 42.37% |\n| MAY 2011 | 1,310 | 3,013 | 43.48% |\n| MAY 2012 | 1,007 | 2,803 | 35.93% |\n| MAY 2013 | 788 | 3,131 | 25.17% |\n| *MAY 20141 | 516 | 2,708 | 19.05% |\n| MAY 2015 | 1,339 | 3,343 | 40.05% |\n| MAY 2016 | 1,776 | 3,984 | 44.58% |\n| MAY 2017 | 2,110 | 5,881 | 35.88% |\n| MAY 2018 | 1,776 | 6,006 | 29.57% |\n| MAY 2019 | 1,153 | 6,204 | 18.58% |\n| *MAY 20212 | 173 | 864 | 20.02% |\n| MAY 2022 | 480 | 1,923 | 24.96% |\n| MAY 2023 | 835 | 2,295 | 36.38% |\n\n\n| OCTOBER |  |  |  |\n| --- | --- | --- | --- |\n| Date of\u003Cbr>Examination | Total\u003Cbr>no. of\u003Cbr>Passed | Total no. of\u003Cbr>Repeater\u003Cbr>Examinees | Passing\u003Cbr>rate |\n| OCT 2010 | 967 | 2,405 | 40.21% |\n| OCT 2011 | 840 | 2,479 | 33.88% |\n| OCT 2012 | 889 | 2,667 | 33.33% |\n| OCT 2013 | 641 | 2,557 | 25.07% |\n| OCT 2014 | 760 | 2,701 | 28.14% |\n| OCT 2015 | 1,071 | 3,583 | 29.89% |\n| OCT 2016 | 773 | 3,740 | 20.67% |\n| OCT 2017 | 642 | 3,765 | 17.05% |\n| OCT 2018 | 501 | 3,666 | 13.67% |\n| OCT 2019 | 413 | 3,960 | 10.43% |\n| *OCT 20213 | 190 | 672 | 28.27% |\n| OCT 2022 | 741 | 2,503 | 29.60% |\n| OCT 2023 | 1,189 | 3,682 | 32.29% |\n\n| MAY |  |  |  |  |\n| --- | --- | --- | --- | --- |\n| ARIMA Model/s | Akaike Information Criterion (AIC) | Bayesian Information Criterion (BIC)/ Schwarz Information Criterion (SIC) | Hannan-Quinn Information Criterion (HQC) | Coefficient of Determination (R squared) |\n| ARIMA (2,1,2) | -1.921769 | -1.760134 | -1.981613 | 0.386913 |\n| ARIMA (2,1,3) | -2.010131 | -1.848495 | -2.069974 | 0.443505 |\n\n\n| OCTOBER |  |  |  |  |\n| --- | --- | --- | --- | --- |\n| ARIMA Model/s | Akaike Information Criterion (AIC) | Bayesian Information Criterion (BIC)/ Schwarz Information Criterion (SIC) | Hannan-Quinn Information Criterion (HQC) | Coefficient of Determination (R squared) |\n| ARIMA (2,1,1) | -2.295426 | -2.133790 | -2.355269 | 0.219264 |\n| ARIMA (2,1,3) | -2.347245 | -2.185610 | -2.407089 | 0.303885 |\n\n\n| MAY |  |  |  |  |\n| --- | --- | --- | --- | --- |\n| ARIMA Model/s | Akaike Information Criterion (AIC) | Bayesian Information Criterion (BIC)/ Schwarz Information Criterion (SIC) | Hannan-Quinn Information Criterion (HQC) | Coefficient of Determination (R squared) |\n| ARIMA (2,1,3) | -1.627302 | -1.465666 | -1.687145 | 0.395445 |\n\n\n| OCTOBER |  |  |  |  |\n| --- | --- | --- | --- | --- |\n| ARIMA Model/s | Akaike Information Criterion (AIC) | Bayesian Information Criterion (BIC)/ Schwarz Information Criterion (SIC) | Hannan-Quinn Information Criterion (HQC) | Coefficient of Determination (R squared) |\n| ARIMA (","cbCaie6Ex0x5FMqJ","https://ap.wps.com/l/cbCaie6Ex0x5FMqJ","pdf",867189,15,"English","# Examination Passing-Rate Data\n## Passing rates for first-timers\n## Passing rates for repeaters\n# ARIMA Model Comparison\n## May examinations\n## October examinations\n## Best-fit model indicators (AIC/BIC/HQC/R²)","[{\"question\":\"What passing-rate data is compiled in the study?\",\"answer\":\"The document lists CP ALE results by examination date (May and October), including total passed, total first-timer (or repeater) examinees, and the resulting passing rate percentages.\"},{\"question\":\"How does the study model forecasting of passing rates?\",\"answer\":\"It uses ARIMA time-series models and tests multiple ARIMA parameter sets to model the passing rate behavior over time for May and October, separately for first-timers and repeaters.\"},{\"question\":\"Which metrics are used to evaluate the ARIMA models?\",\"answer\":\"Model performance is compared using Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC)/Schwarz Information Criterion (SIC), Hannan-Quinn Information Criterion (HQC), and the coefficient of determination (R squared).\"}]","Forecasting the National Passing Rate of the Certified Public Accountant Licensure Examination (CPALE) - ARIMA Model Evaluation | PDF",1788338714,38]