DEPARTMENT OF STATISTICS & DATA SCIENCE
- Introduction
- Facilities
- Academic Programs
- Faculty
INTRODUCTION
Statistical methods and the applications of probability theory are essential to the understanding of data and underlying processes in a very wide variety of fields, including health sciences, economics, and finance. Statistics is considerably more applied and vocational than many other courses. The vision of the department is to promote a quality education and productive research in different fields of Statistics. By extending the contributions in business, industry, and society, we enable our graduates to lead the research community, statistical profession, and society at large.
Department of Statistics is to contribute to the overall objectives of University of Mianwali through excellence in research and education in the Statistical Sciences. We aim to promote and sustain an environment that fosters creativity, critical thought, enquiry, and active learning equity.
BS Statistics
Duration
The duration required to complete this degree is 4 years.
Semesters
Students are required to pass 8 semesters for the completion of this degree.
Credit Hours
Students must complete 124 credit hours for this degree.
Eligibility
At least 45% marks in Intermediate or equivalent
BS Data Science
Duration
The duration required to complete this degree is 4 years.
Semesters
Students are required to pass 8 semesters for the completion of this degree.
Credit Hours
Students must complete 130 credit hours for this degree.
Eligibility
At least 50% marks in Intermediate (HSSC) examination with Mathematics or equivalent qualification with Mathematics and Computer Science, certified by IBCC.
FACULTY
Dr. Faisal Rehman
Incharge/ Assistant Professor
Mr. Faisal Rehman
Lecturer
Mr. Faisal Rehman
Lecturer
Aditional Duties
1. Computer Programmer ( UMW IT Cell/Services )
2. Incharge TimeTable (Department of Computer Science, Information Technology and Software Engineering)
Publications
1. Rehman, Faisal & Malik, M.s.I. & Faisal, Muhaamad. (2019). Significance of Linguistic Indicators for Location Prediction. 1-6. 10.1109/INMIC48123.2019.9022735.
Resarch Interest
• Data Mining
•Machine Learning
•Text Mining
- Email:faisal.rehman@umw.edu.pk
Mr. Aziz Ullah
Visiting Lecturer
Ms. Ume Farwa
Visiting Lecturer