Welcome to the Department of Statistics at Hajee Mohammad Danesh Science and Technology University, Dinajpur, Bagladesh
The purpose of Statistics is to design, construct, and evaluate techniques for analyzing data. The data can be qualitative or quantitative, self-reported or machine-collected, and the motivations can be scientific, commercial, legal, or policy.
The emergence of data science and analytics and the global use of statistical ideas have required us to quickly adapt both our teaching and research.
Since it was established in 1988, there have been many stimulating and creative times in the Department. At present, the Department offers B,Sc (Hons) in Statistics programme, two research postgraduate programmes like MS and PhD degrees.
In about three decades the Department has accommodated high profile faculty members with diverse research areas including statistical theory, big data, biostatistics, epidemiology, design of agricultural experiments, business statistics, social statistics, statistical data mining, and other areas of cross-disciplinary research.
Research in the department focuses on statistical machine learning, computational biology, social sciences, agricultural, econometric and multilevel model. We also have faculty whose research is dedicated to improving the quality of statistics education.
At the present age, Statistics has become an indispensable tool in many diverse branches of natural sciences, medical sciences, social sciences, biomedical sciences, finance, economics, engineering, etc. Our faculty and staff are ready to meet these new challenges. Our goal is always to be nothing less than a world-class statistics department, providing the highest quality education and leading-edge research.
Prof. Dr. Soyeda Jahanara Afroz
Chairman, Department of Statistics (STT).
Mobile No: +8801713163315
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My research interest includes are in theoretical and computational aspects of statistical machine learning, robust statistics, and topological data analysis for multi-view data integration in Biomedical Enginering. Statistical machine learning: dimensionality reduction, feature selection, non-parametric models, and inference methods. Robust ...
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Efficiency, Productivity and Stochastic Analysis, Econometrics, Bio-statistics, Data Mining and Statistical Learning, Support Vector Machine, Multivariate Data Analysis
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Interested to work in any field of Statistics specially Time series, Econometrics, Bio-statistics, Demography.
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Bio-statistics, Social-science, Demography and Time series analysis