Code MATH 306
Term 201703
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) Ozgur Martin -ozgurmartin@sabanciuniv.edu,
Language of Instruction English
Prerequisites
(only for SU students)
MATH203
Mode of Delivery Formal lecture,Recitation
Planned Learning Activities Discussion based learning
Content

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.

Objective

- 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 special sampling distributions
Apply the techniques of point estimation for parameters of interest and assess the quality of these estimators
Construct confidence intervals of parameters of interest

Apply the classical approach to hypothesis testing
Apply and implement special statistical tests
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 in Turkish and English by oral, written, graphical and technological means. 2 5 Take individual and team responsibility, function effectively and respectively as an individual and a member or a leader of a team; and have the skills to work effectively in multi-disciplinary teams. 3 Common Outcomes ForFaculty of Eng. & Natural Sci. 1 Possess sufficient knowledge of mathematics, science and program-specific engineering topics; use theoretical and applied knowledge of these areas in complex engineering problems. 3 2 Identify, define, formulate and solve complex engineering problems; choose and apply suitable analysis and modeling methods for this purpose. 4 3 Develop, choose and use modern techniques and tools that are needed for analysis and solution of complex problems faced in engineering applications; possess knowledge of standards used in engineering applications; use information technologies effectively. 3 4 Ability to design a complex system, process, instrument or a product under realistic constraints and conditions, with the goal of fulfilling specified needs; apply modern design techniques for this purpose. 4 5 Design and conduct experiments, collect data, analyze and interpret the results to investigate complex engineering problems or program-specific research areas. 4 6 Knowledge of business practices such as project management, risk management and change management; awareness on innovation; knowledge of sustainable development. 3 7 Knowledge of impact of engineering solutions in a global, economic, environmental, health and societal context; knowledge of contemporary issues; awareness on legal outcomes of engineering solutions; understanding of professional and ethical responsibility. 2 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 Industrial Engineering Program Outcomes Required Courses 1 Formulate and analyze problems in complex manufacturing and service systems by comprehending and applying the basic tools of industrial engineering such as modeling and optimization, stochastics, statistics. 5 2 Design and develop appropriate analytical solution strategies for problems in integrated production and service systems involving human capital, materials, information, equipment, and energy. 4 3 Implement solution strategies on a computer platform for decision-support purposes by employing effective computational and experimental tools. 3 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. 3 2 Demonstrate knowledge of discrete mathematics and data structures. 2 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. 3 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. 3 Mechatronics Engineering Program Outcomes Area Electives 1 Familiarity with concepts in statistics and optimization, knowledge in basic differential and integral calculus, linear algebra, differential equations, complex variables, multi-variable calculus, as well as physics and computer science, and ability to use this knowledge in modeling, design and analysis of complex dynamical systems containing hardware and software components. 4 2 Ability to work in design, implementation and integration of engineering applications, such as electronic, mechanical, electromechanical, control and computer systems that contain software and hardware components, including sensors, actuators and controllers. 2 Materials Science and Nano Engineering Program Outcomes Area Electives 1 Applying fundamental and advanced knowledge of natural sciences as well as engineering principles to develop and design new materials and establish the relation between internal structure and physical properties using experimental, computational and theoretical tools. 2 2 Merging the existing knowledge on physical properties, design limits and fabrication methods in materials selection for a particular application or to resolve material performance related problems. 2 3 Predicting and understanding the behavior of a material under use in a specific environment knowing the internal structure or vice versa. 3 Electronics Engineering Program Outcomes Area Electives 1 Use mathematics (including derivative and integral calculations, probability and statistics), basic sciences, computer and programming, and electronics engineering knowledge to design and analyze complex electronic circuits, instruments, software and electronics systems with hardware/software. 3 2 Analyze and design communication networks and systems, signal processing algorithms or software using advanced knowledge on differential equations, linear algebra, complex variables and discrete mathematics. 2
 Assessment Methods and Criteria Percentage (%) Exam 100
 Recommended or Required Reading Textbook John E. Freund's Mathematical Statistics with Applications, by I.Miller & M.Miller, 8th ed., Pearson International, 2014.