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This study applies Statistical Process Control (SPC) techniques control charts and process capability indices to evaluate and enhance the academic performance of Ibb University students taught by the researcher from 2017 to 2020 in three foundation courses: Probability Theory, Linear Programming, and Mathematical Statistics. Treating education as a measurable process, the analysis revealed general process stability, with all control charts within limits except for one year when instruction was in English instead of the native language, leading to a spike in failure rates. Once the language issue was addressed, performance improved significantly. The process capability index (Cpk = 1.333) reflects good performance with room for improvement. A nonlinear pattern, termed the \"Hat Relationship,\" shows that success in Mathematical Statistics depends strongly on prior performance in the prerequisite courses. The results underscore the importance of reinforcing foundation-level education to ensure success in advanced subjects. The study recommends adapting industrial metrics like Cpk for educational settings and promotes the use of control charts as practical tools for monitoring and improving the learning process, thereby supporting data-driven decision-making in teaching and curriculum design.

Remittances are vital for economic growth, especially in developing nations like Yemen. However, the phenomenon of forgotten financial remittances poses significant threats to Yemen's financial stability, as these unreceived transfers negatively impact its economy. Therefore, this study aims to identify the main causes of this phenomenon. These causes include logistical and economic factors of senders and beneficiaries, and features of banks and money exchange firms. The study surveyed 931 Yemeni respondents who experienced forgotten financial remittances, answering 15 possible reasons with \"yes\" or \"no\" in the questionnaire. Descriptive statistical measures were employed to characterize the sample, while neural network analysis (NNA) primarily identified the main factors contributing to forgotten financial transfers. The analysis revealed three key dimensions leading to this problem. The first dimension involves communication or access problems between the sender and recipient. The second dimension involves logistical obstacles that hinder remittance flows, including technological, financial, administrative, and bureaucratic challenges. These barriers can be associated with the senders, recipients, or exchange companies. The final dimension is related to the operations of money exchange companies and the uniformity of their rates. To ensure the stability of the results, Bootstrapping technique was utilized based on a random sample of size 500 observations from the original dataset. Thus, the results demonstrated stability and reliability for all samples larger than 30% of the original sample size.