M.Phil Statistics

Introduction

In continuation of the BS Statistics program, further higher training toward research is essential in Pakistan. The Best University in Multan is providing higher research facilities to the students of Southern Punjab in many disciplines in M.Phil. Statistics. ISP is the only institution in Southern Punjab providing this facility with highly qualified and trained faculty. Moreover, ISP is also providing facilities of research to the students in many vacant research areas, so that after completing their degrees they can get jobs.

Eligibility Criteria

Sixteen years of schooling or 4 year education in relevant filed from HEC recognized DAI will be required for admission.
The GAT-General (CAT-C) (www.nts.org.pk/gat/gat.asp) / ISP-Admit Test conducted by the National Testing Service with a minimum 50% cumulative score will be required at the time of admission.

NOC

For M.Phill statistics program NOC is granted by HEC Pakistan.

Career Prospects

Statisticians not only work in academia but also work in many other fields including the following:

Market researcher
Financial risk analyst
Operational researcher
Business analyst
Data scientist
Investment analyst and many others.

Program Educational Objectives (PEOs)

PEO-I

Acquire a sound knowledge and deeper understanding of Statistics and will be able to pursue their studies for Ph.D. in Statistics.

PEO-II

Do research in Statistics as well as related areas of other disciplines.

PEO-III

To read, discuss, write and present Statistics with proper reasoning.

PEO-IV

To work both independently and collaboratively on statistical problems in their own as well as allied areas while demonstrating high ethical values.

PEO-V

Acquire a sound knowledge of latest statistical software, needed in their areas.

PEO-VI

Pursue their professional career in universities, research organizations, Business and Finance, Govt. Departments as well as private organizations, etc.; and will be able to reach middle level management within five years.

Programs Learning Outcomes (PLOs)

PLO-I

To apply knowledge of Statistics and other related areas to the solutions of problems occurring in their own areas as well as related areas of other disciplines.

PLO-II

To identify research literature and formulate statistical problems for further analysis and investigations.

PLO-III

To create, select and apply appropriate methods and techniques for the solution of statistical problems.

PLO-IV

To apply their knowledge of social, health, cultural and economic issues in their professional responsibilities.

PLO-V

To apply high ethical values and norms in their professional careers.

PLO-VI

To work effectively as an individual or as a member of team in multi-disciplinary environment.

PLO-VII

To communicate effectively on statistical ideas and techniques with Statistics community as well as society.

PLO-VIII

To engage in life-long learning in the context of latest advancements in their own and related areas.

Scheme of Studies for M.Phil Statistics Program

Total Credit Hours = 30

Courses
Advanced Probability Theory	Advanced Statistical Inference I	Advanced Design of Experiments	Linear Models and Regression Analysis I
Advanced Statistical Inference II	Linear Models and Regression Analysis II	Advanced Multivariate Analysis	Regression Models for Count Data
Time Series Analysis for Forecasting	Advanced Categorical Data Analysis	Logical Reasoning and Research Methods	Survey Sampling
Longitudinal Data Analysis	Survival Data Analysis	Applied Stochastic Models	Spatial Data Analysis
Advanced Distribution Theory	Inference in Stochastic Processes	Advanced Bayesian Inference	Optimization Techniques
Ecological Statistics	Statistical Methods for Clinical Trials	Bayesian Inference	Financial Stochastic Models
Statistical Genetics	Generalized Linear Models	Meta-Analysis	Decision Trees
Generalized Linear Mixed Models	Advanced Operations Research	Multilevel Modeling	Environmental Statistics
Advanced Statistical Methods in Quality	Applied Smoothing Techniques	Convergence in Probability	Structural Equation Models
Casual Inference	Measure Theory and Integration	Advanced Statistical Theory Thesis	Thesis