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I am a dedicated Research Associate in Data Analysis and Statistics with a strong academic background in statistical modeling, econometrics, and applied data science. Currently pursuing a PhD in Statistics, I specialize in advanced quantitative techniques including regression analysis, time series modeling (ARDL), panel data methods, and Bayesian approaches.
I have hands-on experience working with real-world datasets, particularly in areas such as economic growth, environmental sustainability, and labor market dynamics. My expertise includes using statistical software such as Stata, R, and Python to conduct empirical research, perform diagnostics, and generate policy-relevant insights.
In addition to research, I am actively involved in teaching statistics and biostatistics at the university level, which has strengthened my ability to communicate complex analytical concepts clearly and effectively.
I am passionate about transforming data into meaningful insights and contributing to evidence-based decision-making in academia, policy, and industry.
I have extensive experience in quantitative research, focusing on the application of advanced statistical and econometric techniques to real-world problems. My work primarily involves analyzing large datasets related to economic growth, environmental sustainability, and labor market dynamics. I have applied models such as Ordinary Least Squares (OLS), panel data methods (Fixed and Random Effects), and Autoregressive Distributed Lag (ARDL) models to investigate long-run and short-run relationships among variables.
I am also experienced in Bayesian statistical approaches, integrating prior information with observed data to improve estimation accuracy and provide robust inference. My research contributions emphasize methodological rigor, model diagnostics, and policy-relevant interpretation of results.
Visiting Lecturer – Statistics & Econometrics
At university level, I have been actively teaching courses in statistics, econometrics, and biostatistics. I design and deliver lectures on core topics including hypothesis testing, regression analysis, time series modeling, and statistical inference. I guide students in practical data analysis using software such as Stata and R, helping them build strong analytical and research skills.
Data Analysis & Software Expertise
I have strong hands-on experience with statistical software including Stata, R, and Python for data cleaning, visualization, and advanced modeling. I routinely perform diagnostic tests, model selection, and validation to ensure accuracy and reliability of results. I also prepare research reports, academic papers, and data-driven presentations.
I am currently pursuing a PhD in Statistics with a research focus on advanced econometric modeling and data analysis. My work emphasizes time series techniques (ARDL), panel data models, and Bayesian statistical approaches to study relationships between economic growth, urbanization, and environmental sustainability.
Completed a Master of Science in Statistics with a strong foundation in probability theory, statistical inference, regression analysis, and multivariate methods. My graduate research involved applied econometrics and data-driven analysis using real-world datasets.
