M.Phil Statistics
Build the skills to lead in M.Phil Statistics
Superior University’s M.Phil Statistics program prepares the students to investigate a particular area of study in-depth and conduct research to make a significant contribution to the field. The qualified faculty helps students acquire a wide range of research and transferable skills along with a profound understanding and expertise in their chosen field of research, facilitating their transition into research and academic careers after the completion of their degrees.
Eligibility Criteria
CGPA 2 Out of 4 (as per university and HEC policy)
GAT
3rd party or NTS 50 %, if university then 60% (as per university and HEC policy)
Research areas:
1-BIO-Statistics
2-Business Statistics
3-Data Science
4-Machine Learning
5-Mathematical Statistics
6-Applied Statistical
7-Quality Control
8-Sampling Survey
9-Predictive Analysis
and more.
- Course Duration: 2 Years
- Total Credit Hours: 36
- Semester: 4
Semester 1
| Course | Credit Hours |
|---|---|
| Probability Distributions | 3 |
| Survey Sampling | 3 |
| Elective-I | 3 |
| Elective-II | 3 |
| Total | 12 |
Semester 2
| Course | Credit Hours |
|---|---|
| Statistical Inference | 3 |
| Statistical Analysis by R | 3 |
| Elective-III | 3 |
| Elective-IV | 3 |
| Total | 12 |
Semester 3 & 4
| Course | Credit Hours |
|---|---|
| Research Thesis | 6 |
| Total | 6 |
Elective Courses
| Elective | |
|---|---|
| Advanced Regression Analysis | 3 |
| Advanced Bayesian Inference | 3 |
| Advanced Categorical Data Analysis | 3 |
| Advanced Design of Experiments | 3 |
| Advanced Distribution Theory | 3 |
| Advanced Multivariate Analysis | 3 |
| Advanced Operations Research | 3 |
| Advanced Statistical Methods in Quality control | 3 |
| Applied Smoothing Techniques | 3 |
| Applied Stochastic Models | 3 |
| Bayesian Inference | 3 |
| Causal Inference | 3 |
| Convergence in Probability | 3 |
| Decision Trees | 3 |
| Ecological Statistics | 3 |
| Environmental Statistics | 3 |
| Financial Stochastic Models | 3 |
| Generalized Linear Mixed Models | 3 |
| Generalized Linear Models | 3 |
| Inference in Stochastic Processes | 3 |
| Linear Models | 3 |
| Logical Reasoning and Research Method | 3 |
| Longitudinal Data Analysis | 3 |
| Meta Analysis | 3 |
| Multilevel Modeling | 3 |
| Optimization Techniques | 3 |
| Regression Models for Count Data | 3 |
| Spatial Data Analysis | 3 |
| Statistical Genetics | 3 |
| Statistical Methods for Clinical Trials | 3 |
| Structural Equation Models | 3 |
| Survival Data Analysis Time Series Analysis and Forecasting | 3 3 |
| Total | 99 |
*To accommodate modern trends, Institute may reserve the right to change course requirements, fees, course classifications, course contents, class schedules, venues, faculty and the like, whenever it deems appropriate.
