This course introduces some statistical modeling simulation methods to evaluate the performance of statistical methods. This course emphasizes both the theoretical and the practical aspects of statistical simulations and analysis. The goal is to help the students to develop a solid theoretical background in introductory level of simulation. Moreover most focus on statistical simulation with R software. This course improve the computational ability of students.
- Ross, S.M. (2002). Simulation ( Third Edition) (Academic)
- Velten, K. (2009). Mathematical modeling and simulation. Wiley.
Distribution of Marks:
Mid Exam: 30
Final exam: 50
Sessional (Assignment,Presentation,Participation,Attendance,Quizes) 20
Scheduled on:
BS Regular Monday (11:00-12:00) Tuesday(11:30-12:30) Wednesday (11:00-12:00)
BS Self Support Tuesday(12:30-2:00) Wednesday (2:00-3:30)
| Week | Topics and Readings |
| 1 | Introduction to Simulation and Its types |
| 2 | Introduction to Computer Simulation |
| 3 | Clinical healthcare simulators |
| 4 | Some examples of mathematical modeling and simulation |
| 5 | Monte Carlo methods |
| 6 | Random number generation methods |
| 7 | Generation of random variable |
| 8 | Generation of discrete random variable |
| 9 | Generation of continuous random variable |
| 10 | Generation of discrete random variable using inverse transform and acceptance rejection method |
| 11 | Generation of continuous random variable using inverse transform and acceptance rejection method |
| 12 | Comparison of algorithms to generate random variables |
| 13 | Simulating Descriptive measures of univariate, bivariate and multivariate with R |
| 14 | Simulating one and two variable in testing of hypothesis about correlation coefficients with R |
| 15 | Gibbs sampling |
| 16 | Variance reduction techniques: importance sampling for integration, control variates and antithetic variables |
Course Material
- Total Lessons 16
- Department Statistics
- About Visit Profile
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Teacher
Ms. Sadia Qamar
