Home / Undergraduate courses

 

The Department offers the following programs at undergraduate level:

  • General Degree (3 years)
  • Special Degree in Statistics (4 years)

 

B.Sc. (General) degree

First year

Semester 1

STA 113 2.0 Descriptive Statistics c
STA 114 2.0 Probability and Distribution Theory I c
STA 115 1.0 Elements of Sampling c

 

Semester 2

STA 123 2.0 Probability and Distribution Theory II c
STA 124 2.0 Data Analysis I c
STA 125 1.0 Statistical Communication c

 

Second  year

Semester 1

STA 213 2.0 Inferential Statistics c
STA 214 1.0 Nonparametric Statistics c
STA 215 2.0 Sampling Techniques c

 

Semester 2

STA 224 2.0 Regression Analysis c
STA 225 2.0 Design of Experiments c
STA 226 1.0 Data Analysis II c

 

Third year

Semester 1

STA 312 2.0 Time series analysis c
STA 313 2.0 Statistical decision theory o
STA 314 2.0 Multivariate statistical methods o
STA 316 2.0 Discrete and categorical data analysis c
STA 319 2.0 Advanced regression analysis o
STA 326 2.0 Programming and data analysis with R o
STA 351 2.0 Research methodology o

 

Semester 2

STA 315 2.0 Essential skills in statistics c
STA 321 2.0 Statistical quality assurance o
STA 322 2.0 Medical statistics o
STA 324 2.0 Operations research o
STA 325 2.0 Independent study o#
STA 330 2.0 Data analysis and preparation of reports c
STA 332 2.0 Compilation of official statistics o*
STA 333 2.0 Econometric models o**

 

o#: B.Sc. (general) degree students who have followed STA 351 2.0 Research Methodology can do this course as an optional course

o*: Those who are doing Econometrics as a subject are not allowed to do this course

0**: those who are following B.Sc. (special) degree in Statistics are not allowed to do this course

 

B.Sc. (special) degree

Part 1

Semester 1

STA 312 2.0 Time series analysis c
STA 313 1.0 Statistical decision theory c
STA 314 2.0 Multivariate statistical methods c
STA 316 2.0 Discrete and categorical data analysis c
STA 318 2.0 Advanced distribution theory c
STA 319 2.0 Advanced regression analysis c
STA 326 2.0 Programming and data analysis with R c
STA 351 2.0 Research methodology c
STA 354 2.0 Machine learning 1 o

 

Semester 2

STA 315 2.0 Essential skills in statistics c
STA 317 2.0 Advanced design of experiments c
STA 321 2.0 Statistical quality assurance c
STA 322 2.0 Medical statistics o
STA 323 2.0 Introduction to actuarial statistics o
STA 324 2.0 Operations research o
STA 327 2.0 Theory of multivariate statistics c
STA 329 2.0 Advanced statistical inference c
STA 330 2.0 Data analysis and preparation of reports c
STA 331 2.0 Stochastic processes c
STA 332 2.0 Compilation of official statistics o
STA 355 2.0 Optimization o

 

B.Sc. (special) degree

Part 2

 

STA 471 2.0 Generalized linear and non linear models c
STA 472 2.0 Special topics in statistics o
STA 474 2.0 Statistical consultancy c
STA 476 2.0 Statistical data mining c
STA 477 2.0 Spatial statistics o
STA 478 2.0 Advanced time series analysis c
STA 479 2.0 Advanced sampling theory c
STA 480 2.0 Current topics in statistics o
STA 481 2.0 Seminar c
STA 483 6.0 Research project c
STA 484 4.0 Internship c
STA 485 2.0 Measure theory o
STA 486 2.0 Survival analysis o
STA 487 2.0 Computational inference o
STA 490 2.0 Linear mixed models and generalized linear mixed models c
STA 491 2.0 Bayesian inference o