** M.Sc. and PG.Dip. in Applied Statistics**

The program consists of three parts, namely, **Part 1**, **Part II** and **Part III**.

**Part 1** consists of 5 course units worth of 5 credits, which introduce elementary statistics and probability with minimal application of mathematics. Contents are restricted to standard applications of statistics without much theory.

**Part II** consists of 10 course units worth of 15 credits, which introduce essential statistical methods with basic theory without much mathematical proofs.

**Part III** consists of 5 course units worth of 10 credits and a research project worth of 450 credits. In this part students will learn advanced statistical theory and techniques.

Total program, including lectures and examinations, requires approximately 92 working Saturdays. Total duration of the M.Sc. program is approximately 2 years. The lengths of parts 1, 2, and 3 are approximately 4 months, 12 months, and 8 months, respectively.

#### Part I

STA 501 1.0 Elements of Probability and Descriptive Statistics

STA 502 1.0 Elements of Sample Surveys

STA 503 1.0 Elements of Statistical Inference

STA 504 1.0 Elements of Statistical Modelling

STA 505 1.0 Elementary Data analysis

STA 501 1.0 Elements of Probability and Descriptive Statistics

STA 502 1.0 Elements of Sample Surveys

STA 503 1.0 Elements of Statistical Inference

STA 504 1.0 Elements of Statistical Modelling

STA 505 1.0 Elementary Data analysis

#### Part II

STA 506 2.0 Linear Regression Analysis

STA 507 2.0 Design and Analysis of Experiments

STA 508 2.0 Time Series Analysis

STA 509 1.5 Generalized linear models

STA 510 1.5 Sampling Methods

STA 511 1.5 Categorical Data Analysis

STA 512 1.5 Data analysis and Statistical Computing

STA 513 1.0 Medical Statistics

STA 514 1.0 Industrial Statistics

STA 515 1.0 Actuarial Statistics

#### Part III

STA 516 2.5 Advanced Probability and distribution Theory

STA 517 2.5 Advanced Statistical Inference

STA 518 2.0 Multivariate Statistics

STA 519 2.0 Data analysis and Statistical Computing

STA 520 1.0 Research Methodology

30.0 Research Project