Department of Statistics

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Author: search.filters.author.Dr. Muhammad Noor-ul-Amin

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    Hybrid Exponentially Weighted Moving Average Control Chart Using Ranked Set Sampling
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2018) Navara Shabbir; SP17-RST-001; LHR TP 5301; Dr. Muhammad Noor-ul-Amin
    In manufacturing process, the products are subjected to variations which directly impact the quality of a product e.g. in the process of filling juice bottles, the amount of juice filled may not exactly the same. Quality control combined with statistical techniques is called statistical process control (SPC). To achieve the level of perfection in a production procedure SPC play an important role, it generally contains tools for monitoring the dissimilarities caused during a production process. SPC has a direct impact in increasing the quality of a product by reducing the amount of variation and enabling it to attain desired satisfaction level.
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    INTERNSHIP ON AUR-LAB
    (Library Information Services COMSATS University Islamabad Lahore Campus, 2024-04-02) Muhammad Samran; FA20-BST-003; Dr. Muhammad Noor-ul-Amin
    AUR-LAB is a collaboration between Superior University, which is presently ranked first in Pakistan for effect among private universities (QS Ranking), and we Plan, an Australian design business based in Pakistan. Within 10 months of its inception, one of its startup initiatives was selected as one of the top two out of about 100+ proposals from Pakistan in the Venture Cup International competition. Current projects include archaeological tourism, Metaverse, NFT Marketplace, governance and voting, fashion design, healthcare, Smart Agriculture, ecological tourism, architectural design, AR-based advertising, energy efficiency, road safety, gender equality, and land revenue. Dr. Muhammad Ashraf Khan, Prof. Saleem Zubair, Ms. Qurratulain Sonia Kashmiri, Mr. Muhmmad Ahmad, Mr. Jawad Ahmad, and Mr. Javaid Iqbal are among our technical and business development professionals.
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    Induction of Measurement Error in Acceptance Sampling Plans
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2019) Sajid Ali Naqvi; SP17-RST-004; LHR TP 5741; Dr. Muhammad Noor-ul-Amin
    Measurement error practically exists to a certain degree and part and parcel of measurement process for quantitative observations. Measurement error cause contamination and result in ineffectiveness of the scale sampling plan. In present study the effect of measurement error is investigated for EWMA based scale sampling plan using a linear covariate method when population standard deviation is known or unknown. The same effect is also examined in the presence of auxiliary information when measurement of quality characteristic is not feasible or accessible. Multiple measurements method is a remedy to minimize the effect of measurement error. The variance of measurement error component becomes zero for infinite number of multiple measurements. A reasonable and economical number of multiple measurements may restore the effectiveness and utilization of EWMA based scale sampling plans with or without auxiliary information when population standard deviation is known or unknown. Tables are provided for various values of model parameters for industrial use
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    Understanding Household Characteristics and Wealth Distribution
    (Library Information Services, COMSATS University Islamabad, Lahore Campus., 2020-04-01) Husnain Ali Sher; CIIT/FA20-BST-005/LHR; Dr. Muhammad Noor-ul-Amin; LHR TP 9950
    The great thing about this research is that it provides in-depth analysis regarding household dynamics, socio-economic disparities, and the impact of modern amenities on daily life within a community. Using several sophisticated machine learning techniques, statistical modeling, and rigorous data analysis, we attempted to identify the characteristics of these households and their corresponding socio-economic environment. This is followed by the study’s objectives, and how crucial household characteristics are in the context of today’s world. It is concerned with the spread and import of houses having internet connections, refrigerators, and televisions. The study applies machine learning models based on neural networks and SVM for regression as follows. international sharing that provides the results and discussion of prediction for household characteristic ownership of modern amenities as we might expect, there was a strong correlation between the wealth of the household and possessions: the richer they were, the more amenities people had. The educational qualification of the household head also continued to be a significant determinant in terms of socio economic achievements and ownership of modern amenities. The most important and outstanding characteristics are education for linear ones and households. Multiple regression analysis was used to predict outcomes. The model reveals that the highest levels of education for household heads indicate positive signs of socioeconomic status and ownership of modern amenities. The machine learning models often gave me little extra insights Nevertheless there are a few limitations and challenges since family dynamics in the neural network model may be overfitting. These models helped to explore predictors of household behavior leading to understanding socio-economic factors on modern facilities ownership. This research highlights the importance of contemporary amenities in households and their association with socio-economic status. Our study findings underscore the importance of working not only to further educational opportunities but also to be more active in ensuring access and education around digital connectivity, which is a critical stepping-stone for fairer development and improved quality of life.
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    Determinants of Child Mortality in Punjab, Pakistan
    (Library Information Services, COMSATS University Islamabad, Lahore Campus., 2020-04-01) Kashaf Zahra; CIIT/FA20-BST-006/LHR; Dr. Muhammad Noor-ul-Amin; LHR TP 9951
    This research project examines the key determinants of child mortality in Punjab, Pakistan, focusing on factors such as birth order, mother’s age at birth, birth interval, premature birth, and multiple births. These findings indicate that firstborn and higher-order children exhibit higher mortality rates, which are attributed to inexperienced parenting in the case of firstborns and the dispersion of resources among siblings for higher-order children. The study showed that children born to mothers aged between 20-34 years had the highest survival rates than children born to mothers who are teenagers or mothers above 34 years. This means that the families mothers give birth within the age interval 20-34 are more likely to have low mortality rates hence the need to encourage family planning. It was also observed that both premature and multiple births are associated with high mortality rates hence there is a need to enhance quality perinatal and neonatal services. It is recommended that the Ministry of Health focuses on streamlined health policies, enhanced awareness of parents, and improved supply of resources to decrease infant mortality and promote general child health in the area. Integrated approaches, awareness campaigns, and the improvement of education and health care as well as the establishment of favorable policies are indispensable to tackle the multifaceted problem of child mortality.
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    Data-Driven Sample Size Adaptation in EWMA Control Chart for Improved Monitoring
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2025) Gulmakai; CIIT/FA23-RST-002/LHR; Dr. Muhammad Noor-ul-Amin; LHR TP 9873
    Statistical Process Control (SPC) serves as a fundamental methodology for monitoring and maintaining stability in manufacturing processes. In this study, an Adaptive Sample Size-based Exponentially Weighted Moving Average (ASEWMA) control chart is proposed to enhance the detection of process shifts by dynamically adjusting the sample size in response to observed process behavior. The adaptability of the sample size enables the control chart to respond more efficiently to both small and moderate shifts while conserving computational and sampling resources when the process is stable. Further, the proposed control chart is evaluated in the presence of measurement error. The performance of the ASEWMA control chart is rigorously evaluated through extensive Monte Carlo simulations. Key performance indicators such as the Average Run Length (ARL) and Standard Deviation of Run Length (SDRL) are employed to assess its effectiveness in various shift scenarios. Comparative analyses demonstrate that the ASEWMA chart consistently outperforms traditional control charts, including the Fixed Sample Size EWMA (FEWMA) and Variable Sample Size EWMA (VEWMA), particularly in detecting small shifts in the process mean. The findings of this research highlight the ASEWMA chart’s potential to provide a practical and efficient tool for quality monitoring in industrial settings. By achieving a desirable balance between sensitivity to shifts and computational efficiency, the proposed method facilitates the timely detection of process changes while maintaining robustness under in-control conditions