MS Applied Statistics – UMT

Course Name:    MS Applied Statistics

Overview:    

The economy of Pakistan is facing many modern day challenges and to meet these challenges we need to have highly qualified professionals in statistical data analysis as in today’s business world information is replacing the physical objects. The School of Business and Economics at UMT plans to play a significant role to cope with the challenges by producing academically and technically more qualified human-power in Statistics. This program is designed to equip students with an excellent knowledge of statistical principles and methods required by practicing statisticians and also focused on developing skills in Applied Statistics.

Number of Semesters:    4

Requirements

Sixteen years of education and Cumulative Grade Point Average (CGPA) of 2.5 out of 4 in BS (Statistics/Mathematics/Economics) / MSc or equivalent. Clearance of GAT with minimum 50% score. Result of GAT can be provided within 6 months of after getting the admission. All academic credentials must be attached with the admission form and interview panel (PhD Committee members) will give the final decision regarding admission in MS in Applied Statistics.

Course Duration:     2 years

How to apply:

• Applicant
  
  • Issuance of Admission form
    
• Fill in Application form
  
• Submit to Admission Office
  
  • Completely filled Application form
    
  • 4 – Photographs
    
  • Photocopies of all Academic Doc’s
    
• Checked by Admission officer
  
  • Approved to the Admission Test
    
  • Admit card
    
• Test & Interview
  
  • NTS/UMT Entry test
    
  • Interview
    
• Merit list
  
  • Accepted candidates
    
• Fee Submission
  
  • Submit Admission & Library Charges
    
  • First Installment of Tuition Fee
    
• Orientation
  

Curriculum:

Core Courses

• Research Methodology
  
• Statistical Analysis for Applied Statistics
  
• Experimental Designs
  
• Survey and Sampling Techniques
  
• Multivariate Analysis
  

Elective Courses (Any Three)

• Population and Demographic Analysis
  
• Advanced Quantitative Techniques
  
• Stochastic Processes
  
• Financial Engineering
  
• Regression and Econometric Analysis
  
• Actuarial Statistics
  
• Reliability Analysis
  
• Survival Analysis
  
• Big Data Analysis
  
• Cloud Computing
  
• R Language
  
• Python
  
• SAS
  
• Mat-Lab
  
• Mathematics
  

MS Thesis

Thesis shall be of 06 credit hours. A participant shall be allowed to start working on thesis after completing the course work of 24 credit hours with a min. CGPA of 3 out of 4.