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MODELING THE EFFECT OF PRIOR STATISTICAL KNOWLEDGE ON ACADEMIC PERFORMANCE USING REGRESSION ANALYSIS

Ahlam Ali Alzharani

Advances and Applications in Statistics2026https://doi.org/10.17654/0972361726018article
ABDC C
Weight
0.50

What the paper says

This study investigates the effect of prior statistical knowledge on the academic performance of business college students. Some business colleges admit students without any statistical background, even though most business curricula include statistic course. Therefore, a questionnaire was used to gain insights into students’ academic performance based on their prior statistical knowledge. The main results indicate that students with a statistical background demonstrate greater confidence in using analytical tools and higher academic scores in business core courses. These results suggest that introducing statistics early in the curriculum enhances academic performance and analytical skills. Strengthening statistical preparation before and during business programs can contribute to producing high-quality graduates who meet labor market requirements, while also aligning with the objectives of Saudi Vision 2030.

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https://doi.org/https://doi.org/10.17654/0972361726018

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@article{ahlam2026,
  title        = {{MODELING THE EFFECT OF PRIOR STATISTICAL KNOWLEDGE ON ACADEMIC PERFORMANCE USING REGRESSION ANALYSIS}},
  author       = {Ahlam Ali Alzharani},
  journal      = {Advances and Applications in Statistics},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.17654/0972361726018},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.