Department of Statistics
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Item INTERNSHIP REPORT ON BAIG ELECTRICAL COMPANY (PVT.) LIMITED(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2025) Fakhra Manzoor; CIIT/FA21-BST-009/LHR; Dr. Riffat Jabeen; LHR TP 9957When I was working as an intern in Baig Electrical Company (Pvt.) Ltd., I was blessed to work with an organization that was electrical based and I was able to develop on several of these skills. The type of tasks included data entry and auditing; in this way, I gained knowledge of the finance department. The management practices that were explained to me were useful in realizing that people have various responsibilities within a firm. I have appreciated various aspects of how a business runs and the many roles I can take on depending on the sector. In the course of my internment, I engaged myself with multiple exercises that were entirely a new and unique experience to me. They allowed me to participate in testing processes, which provided me with practical experience that I needed. I also came to appreciate quality assurance and got to deal with transformers and switch gears, which I found out are among the company’s biggest brands in the market. This exposure has given me this information on the competition in the electrical sector. I understood the importance of product quality and safety standards in situation to the electrical field which are the critical factor of electrical products and systems’ reliability and safety. It equipped me with technical know-how in and out, soft skills as a team player, good communicator and critical thinker.Item A study of ordered random variables for Reflected Power Function Distribution(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2024) Maydah Azhar; CIIT/FA20-BST-008/LHR; Dr. Riffat Jabeen; LHR TP 9953This thesis presents a comprehensive study of ordered random variables for the Reflected Power Function Distribution (RPFD). The primary focus is on the statistical properties, parameter estimation methods, and applications of the RPFD. The RPFD is a transformation of the traditional Power Function Distribution, which is frequently used to model phenomena in various fields such as hydrology, economics, and engineering. By reflecting the distribution around its midpoint, the RPFD provides a mirrored perspective that is particularly useful for scenarios where probabilities are skewed in the opposite direction. The study begins with an introduction to the Power Function Distribution and its reflection to form the RPFD. The properties of the RPFD, including its probability density function, survival function, hazard rate function, and moments, are thoroughly explored. Various parameter estimation techniques such as Maximum Likelihood Method (MLM), Modified Maximum Likelihood Method (MMLM), and percentile-based estimators are discussed in detail. Furthermore, the thesis delves into generalized order statistics (GOS) and their specific application to the RPFD. This includes the derivation of the probability density function (PDF) and joint PDF for GOS, as well as the calculation of mean, variance, and covariance for different scenarios. The literature review highlights key studies and methodologies that have contributed to the development and understanding of order statistics and RPFD. Empirical analysis using real-life data sets demonstrates the practical utility and superior performance of the RPFD compared to other models. Overall, this research contributes to the statistical theory by providing new insights and tools for the application of the RPFD in various scientific and engineering disciplines.Item Some Memory Type Estimators for Population Variance in Survey Sampling(Library Information Services, COMSATS University Islamabad, Lahore Campus, 2025) Umme Habiba; CIIT/FA23/RST/004/LHR; Dr. Riffat Jabeen; LHR TP 9874Reducing and estimating population variation is important in survey sampling. These variations can occur in any sampling design, including stratified random sampling. In stratified random sampling the difference in stratum weights increase the variation. This problem can be control with the use of calibration techniques, and auxiliary information. By using this technique, we can increase the accuracy and efficiency of estimator. Improving the efficiency of estimator for population variance estimation is the primary goal of this study. Both exponentially weighted moving average (EWMA) and extended exponentially weighted moving average (EEWMA) memory type statistics are used in this study to estimate population variance. EWMA use only current data whereas EEWMA use both current and past observations. The EWMA and EEWMA statistics are used to build the calibration variance and ratio estimators. The mean square errors are calculated, and the effectiveness of the estimators is illustrated through a discussion of mathematical comparisons. To assess the efficiency of the proposed memory type estimators, a simulation study is conducted and MSE are compare with existing estimators. The results show that proposed estimators are perform efficiently as compared to the existing estimators