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Code MATH 306
Term 201402
Title Statistical Modelling
Faculty Faculty of Engineering and Natural Sciences
Subject Mathematics(MATH)
SU Credit 3
ECTS Credit 6.00 / 6.00 ECTS (for students admitted in the 2013-14 Academic Year or following years)
Instructor(s) Jakob Geluk,
Language of Instruction English
Level of Course Undergraduate
Type of Course Click here to view.
(only for SU students)
Mode of Delivery Formal lecture,Recitation
Planned Learning Activities Task based learning

Statistical inference; estimation, confidence intervals, hypothesis testing; analysis of variance; goodness of fit tests; regression and correlation analysis; Bayesian methods; introduction to design of experiments; use of statistical software.


- To introduce the basic techniques of point and interval estimation
- To teach how to design and test hypotheses
- To teach the principles of regression analysis

Learning Outcome

Identify the sampling distributions of means and variances computed from samples

Describe the point estimation, apply the techniques for estimation of parameters of interest
Ability to construct confidence intervals of parameters of interest

Describe the Classical approach to hypothesis testing and have understanding of p-values.
Describe where to apply, and compute, certain statistical tests and demonstrate understanding of the output of statistical software
Interpret the results of certain statistical tests in the context of a theory in core disciplines.
Fit and interpret linear regression models.

Programme Outcomes
Common Outcomes For All Programs
1 Understand the world, their country, their society, as well as themselves and have awareness of ethical problems, social rights, values and responsibility to the self and to others. 2
2 Understand different disciplines from natural and social sciences to mathematics and art, and develop interdisciplinary approaches in thinking and practice. 4
3 Think critically, follow innovations and developments in science and technology, demonstrate personal and organizational entrepreneurship and engage in life-long learning in various subjects. 2
4 Communicate effectively by oral, written, graphical and technological means and have competency in English. 2
5 Take individual and team responsibility, function effectively and respectively as an individual and a member or a leader of a team. 3
Common Outcomes ForFaculty of Eng. & Natural Sci.
1 Possess and apply knowledge of mathematics, science, and engineering. 5
2 Design and conduct research, do experiments, as well as analyze and interpret data. 3
3 Identify, formulate, and solve engineering problems. 2
4 Use the techniques, skills, and modern engineering tools necessary for engineering practice. 2
5 Analyze, design and model engineering systems, components and processes. 1
Common Outcomes ForFaculty of Arts & Social Sci.
1 Develop a thorough knowledge of theories, concepts, and research methods in the field and apply them in research design and data analysis. 3
2 Assess the impact of the economic, social, and political environment from a global, national and regional level. 4
3 Know how to access written and visual, primary and secondary sources of information, interpret concepts and data from a variety of sources in developing disciplinary and interdisciplinary analyses. 3
Common Outcomes ForSchool of Management
1 Demonstrate an understanding of economics, and main functional areas of management. 2
2 Assess the impact of the economic, social, and political environment from a global, national and regional level. 2
Manufacturing Systems Engineering Program Outcomes Required Courses
1 Formulate and analyze problems in complex manufacturing and service systems by comprehending and applying the basic principles of a broad range of fundamental subjects of the discipline including manufacturing processes, service systems design and operation, production planning and control, modeling and optimization, stochastics, statistics. 2
2 Develop appropriate analytical solution strategies for problems in integrated production and service systems involving human capital, materials, information, equipment, and energy. 1
3 Implement solution strategies on a computer platform for decision-support purposes by employing effective computational and experimental tools. 1
Economics Program Outcomes Required Courses
1 Provide constructive analysis of economic phenomena at the national and international level, and interactions between the two. 4
2 Develop an understanding of organizations and institutions in the society as well as their influence on the economy. 2
3 Recognize how incentives shape the behavior of individuals and organizations. 1
4 Identify ?economic? problems and propose alternative models and/or design and conduct research to provide viable solutions using theoretical tools and/or quantitative methods. 4
5 Communicate problems and solutions to managerial and policy decision-making units as well as to lay audiences. 2
Computer Science and Engineering Program Outcomes Core Electives
1 Design, implement, test, and evaluate a computer system, component, or algorithm to meet desired needs and to solve a computational problem. 1
2 Demonstrate knowledge of discrete mathematics and data structures. 1
3 Demonstrate knowledge of probability and statistics, including applications appropriate to computer science and engineering. 5
Molecular Biology, Genetics and Bioengineering Program Outcomes Core Electives
1 Comprehend key concepts in biology and physiology, with emphasis on molecular genetics, biochemistry and molecular and cell biology as well as advanced mathematics and statistics. 1
2 Develop conceptual background for interfacing of biology with engineering for a professional awareness of contemporary biological research questions and the experimental and theoretical methods used to address them. 1
Assessment Methods and Criteria
  Percentage (%)
Final 30
Midterm 60
Participation 10
Recommended or Required Reading

Textbook :
John E.Reund's Mathematical Statistics with Applications, by I.Miller & M.Miller, 8th ed., Pearson International, 2004.

Supplementary Reading :

Mathematical Statistics with Applications by Wackerly & Mendenhall and Scheaffer,6th ed.
Duxbury Advanced Series, 2002.