MS Statistics & Scientific Computing

Department

Computer Science

Level

Graduate

College

College of Computer Sciences & Information Systems

Course Detail

The MS program in Statistics & Scientific Computing develops rigorous foundational mathematical and statistical tools that help in careers as researchers and solution providers.

The MS program in Statistics & Scientific Computing prepares students for careers in research, applications, and teaching. Students choose courses from two areas of concentration for their coursework: Statistics and Computations. The program is designed in accordance with the guidelines of the Higher Education Commission (HEC). It spans a minimum duration of two years, comprising at least four semesters, and requires the successful completion of 32 credit hours. Students must maintain a CGPA of 3.0 for the conferment of the degree.

 

MS Statistics & Scientific Computing students learn to:

  • Develop a thorough understanding of statistical methodology before applying statistical skills to solve real-life problems
  • Apply rigorous statistical techniques to handle data and obtain meaningful results
  • Select and transform data to increase its usefulness for solving particular problems
  • Create information visualizations for data exploration and presentation
  • Establish and understand a connection between the techniques of data analysis and scientific computing and their link with real-life data

1. Knowledge of how to apply statistical and scientific computing techniques and algorithms to real-life datasets to extract meaningful insights.
2. Acquisition of hands-on experience with relevant software tools, languages, data models, and environments for data processing.
3. Ability to communicate results of analysis effectively, both visually and verbally, to a broad audience in the fields of biology, environment, finance and risk management, data science, business management, and other
disciplines.

1. Big Data Analyst 2. Budget Analyst 3. Business Metrics Analyst

4. Economist 5. Financial Analyst 6. Operations Research Analyst

1. Banking and Financial Institutions

2. Government Statistical and Planning Agencies 

3. Insurance and Actuarial Firms

4. Consulting and Business Analytics Firms

5. Technology Companies and Software Houses

6. Healthcare and Pharmaceutical Organizations

7. Manufacturing and Quality Control Organizations

8. Research Organizations and Think Tanks

9. Universities and Higher Education Institutions

16 Years of education in Computer Science, Engineering, Mathematics, Statistics, or any other relevant field.
Minimum CGPA of 2.5 (on a scale of 4.0).
A student selected for admission having a degree other than statistics may be required to study a maximum of
FOUR courses as deficiency courses, which must be passed in the first two semesters. A student cannot register in
MS courses unless all specified deficiency courses have been passed.

To fulfill the degree requirements, students must complete eight taught courses along with 6 credit hours of research thesis for MS by Thesis, or 6 credit hours of Independent Research Studies, namely IRS-I and IRS-II, for MS by Independent Research Study, or 6 credit hours through two courses, Elective IV and Elective V, each
carrying 3 credit hours, for MS by Coursework. The MS by Coursework option shall be subject to the approval of the departmental committee. For MS Thesis requirement, the students must refer to the MS Policy Manual available at https://basr.iobm.edu.pk/ms-mphil-and-phd-policy-and-thesis/

Course Code Course Title Credit Hours
CSP 511 Research Methodology 3+0
STS 601 Advanced Statistical Inference 3+0
STS 602 Mathematical Statistics 3+0
STS 612 Advanced Numerical Computing 3+0
STS611 Statistical Modeling & Computing 3+0

Course Code

Course Title

Credit Hours

Course Code

Course Title

Credit Hours

Statistics Concentration

STS 631

Advanced Design of Experiments

3+0

STS 622

Time Series Analysis

3+0

STS 641

Stochastic Processes

3+0

STS 621

Applied Regression Models

3+0

STS 623

Theory & Practice of Forecasting

3+0

STS 632

Statistical Quality Control

3+0

STS 651

Survey Sampling

3+0

 STS 652

Advanced Distribution Theory

3+0

Computer Concentration

CSP 534

Fundamental of Algorithms

3+0

CSP 585

Information Retrieval & Data Mining

3+0

CSP 632

Decision Theory

3+0

CSP 588

Machine Learning

3+0

DSP 584

Pattern Recognition

3+0

CSP 633

Simulation & Modeling

3+0

CSP 581

Advanced Artificial Intelligence

3+0

 

 

 

 

 

 

Note: Students must select at least three electives from the above list

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

General Completion Requirement (in case coursework is not selected)

STS 691

MS Thesis-I

6+0

STS 692

MS Thesis – II

3+0

STS 693

Independent Research Study – I

3+0

STS 694

Independent Research Study – II

3+0

 

 

Note: Students must choose either the MS Thesis, the Independent Research Study, or two elective courses from the Elective Courses List. If a student opts for the MS Thesis, enrollment in MS Thesis–II is mandatory to maintain continuous registration until the thesis is formally submitted to the Board of Advanced Studies and Research (BASR) for further processing

MS Thesis–II ensures continuous registration until the student’s research thesis is formally submitted to BASR for further processing.

 

Course Structure

Semester One

Research Methodology

Mathematical Statistics

Advanced Numerical Computing

Elective I

Semester Two

Statistical Modeling & Computing

Advanced Statistical Inference

Elective II

Elective III

 

Semester Three

IRS-1/ Elective IV */ MS Thesis-I

Understanding of Holy Quran-I **/ Comparative Religion-I **

Semester Four

IRS – II / and Elective V * / MS Thesis-II

Understanding of Holy Quran-II **/ Comparative Religion-II **

 

* Subject to the approval of departmental committee

** Muslim students are required to take Understanding of Holy Quran I (1 Credit hour) and Understanding of the Holy Quran II (1 Credit hour) and Non-Muslim students are required to take Comparative Religion-I and Comparative Religion-II.