FACULTY OF ARTS AND SCIENCES THE DEPARTMENT OF STATISTICS AND COMPUTER SCIENCES
UNDERGRADUATE COURSE DESCRIPTIONS

MA101 Calculus-I

Type of Course: Lecture+Problem Sessions
Year:
1
Semester: Fall
Credits:4 (3+2+0)
Instructor: Prof. Dr. Abdülkadir Özdeğer

Objective and Contents:
To introduce the basic concepts of differential calculus. Classification of real numbers, complex numbers.  Sequences and series. Tests for convergence and divergence of series, power series. Functions, domain and range. Functions of a single variable. Classification of functions. Limits, continuity and related theorems. Derivatives, differentials. Rolle’s Theorem, Mean Value Theorem. Indeterminate forms, L’Hospital’s Rule. Taylor and Mac-laurin series. Local and absolute maxima and minima of functions. Curve sketching.

Textbook/Recommended Reading :
Thomas’s Calculus, 10 th. Ed., Addison - Wesley, 2001.
Calculus, H.Anton, 6 th. Ed., John Wiley, 1999.
Calculus, Tom M. Apostol, Vol.1, Vol.2, Blaisdell pub. Co., New York, 1961.
Schaum’s outline of theory and problems, E.Passow, Mc-Graw-Hill, 1999.

Teaching Methods: Lecturing and problem sessions.

Assessment tools: Homework, two midterm exams and final exam.

Instruction Language: English

 

SC-101 Introduction to Statistics

Type of Course: Lecture
Year:1
Semester: Fall
Credits:3 (3+0+0)
Instructor:Assoc. Prof. Dr. Fazıl Güler

Objective and Contents:
Introduction to Statistics includes descriptive statistics which focuses on developing graphical and numerical summaries and partial inferential statistics which uses these numerical summaries to assist in decision making. Introduction to statistics, fundamental elements of statistics, types of data, collecting data, reliability and validity of data. Measures of central tendency: Arithmetic, geometric and squared mean for grouped and ungrouped data, median and mode for grouped and ungrouped data, properties of measures of central tendency, selecting of measure of central tendency. Measures of dispersion: The variance, the standard deviation, the coefficient of variation.  Index numbers, fixed base and link relatives index numbers, relations between fixed base and link relatives index numbers, determination of weights, composite index numbers, Laspeyres price index numbers, Paasche price index numbers, Fischer price index numbers , specific use of index numbers ( rotate to real prices from current prices). Probability: Concepts of events, sample spaces and probability, unions and intersections, complementary events, conditional probability, discrete and continuous probability distributions, random variable, probability distribution expected value, The Binominal probability distribution, Hypergeometric distribution, Poisson distribution, The Normal distribution, standard normal distribution.

Textbook/Recommended Reading:
Statistics, J.T. McClave and T. Sincich, 8th. Ed., Prentice Hall, 2000.

Teaching Methods: Classroom discussion

Assessment tools: Midterm exam, Final exam

Instruction Language: English


MA 103 Linear Algebra

Type of Course: Lecture
Year:1
Semester: Fall
Credits:3 (3+0+0)
Instructor: Asst. Prof. Dr. Nebi Önder

Objective and Contents:
To develop the theory of matrices, determinants and apply them to mathematical and physical problems. Matrices, determinants. Inverse of a matrix. Systems of linear equations. Matrix equations. Eigenvalues and eigenvectors of symmetric matrices, diagonalisation of a matrix. Vector spaces and subspaces, Basis and dimension of a vector space.

Textbook/Recommended Reading :
Linear Algebra and Its Applications, D.C. Lay, 2nd. Ed., Addison-Wesley, 2000.
A First Course in Linear Algebra, D.Zelinsky, Academic Press, New York.

Teaching Methods: Lecturing and problem sessions.

Assessment tools: Homework, two midterm exams and final exam.

Instruction Language: English


EC 131 Economics-I

Type of Course: Lecture
Year:1
Semester: Fall
Credits:3 (3+0+0)
Instructor:Assoc. Prof. Dr. Hüseyin Bilgin

Objective and Contents:
To provide the students of economics, business, and finance with the basic principles, laws and concepts of economics. This course helps build a background for the students who should later master deeper fields of economics such as macroeconomics, microeconomics, growth, international economics and others. To provide the students of other fields who will not continue studies on economics, with general, basic insights into economics. Introduction and basic concepts in economics: the subject matter, tools, methods of economics, demand and supply; Introduction to Macroeconomics: National income concepts and accounting, business cycles and economic ailments, determination of national income, aggregate demand and aggregate supply approaches.

Textbook/Recommended Reading:
Economics, Principles, Problems, and Policies, Campbell R. McConnell and Stanley L. Brue, Irwin and McGraw-Hill, Boston, 1999.
Economics Today, Roger LeRoy Miller, Addison-Wesley, Massachusetts, 2000.

Teaching Methods: Lecture/classroom discussions

Assessment tools: Quizzes, midterm exam, final exam

Instruction Language: English


TD 121 Türk Dili-I

Type of Course: Lecture
Year:1
Semester: Fall
Credits:2 (2+0+0)
Instructor:Esra Dicle

Objective and Contents:
Öğrencilerin Türkçe’yi doğru ve düzgün biçimde kullanmalarını sağlamak.Dil kuramları, dillerin doğuşu ve dil-kültür ilişkisi; Türkçe’nin dahil olduğu Ural-Altay dil ailesine özel bir vurgu yapılarak dillerin sınıflandırılması; dilbilimin dört temel dalı olan sesbilim, biçimbilim, söz dizimi ve anlambilimin incelenmesi; Türkçe’nin ses yapısı, sözcüklerin yapısı (ek, kök, gövde, vs.), cümle yapısı; deneme, şiir, roman, öykü gibi seçilmiş kitapların incelenmesi.

Textbook/Recommended Reading :
Çağdaş Türk Dili, Suer Eker

Teaching Methods: Lecture

Assessment tools: Homework, two midterm exams and final exam.

Instruction Language: Turkish.

 

MA 103 Linear Algebra

Type of Course: Lecture
Year:1
Semester: Fall
Credits:3 (3+0+0)
Instructor:Asst. Prof. Dr. Nebi Önder

Objective and Contents:
To develop the theory of matrices, determinants and apply them to mathematical and physical problems. Matrices, determinants. Inverse of a matrix. Systems of linear equations. Matrix equations. Eigenvalues and eigenvectors of symmetric matrices, diagonalisation of a matrix. Vector spaces and subspaces, Basis and dimension of a vector space.

Textbook/Recommended Reading :
Linear Algebra and Its Applications, D.C. Lay, 2nd. Ed., Addison-Wesley, 2000.
A First Course in Linear Algebra, D.Zelinsky, Academic Press, New York.

Teaching Methods: Lecturing and problem sessions.

Assessment tools: Homework, two midterm exams and final exam.

Instruction Language: English


EC 131 Economics-I

Type of Course: Lecture
Year:1
Semester: Fall
Credits:3 (3+0+0)
Instructor: Assoc. Prof. Dr. Hüseyin Bilgin

Objective and Contents:
To provide the students of economics, business, and finance with the basic principles, laws and concepts of economics. This course helps build a background for the students who should later master deeper fields of economics such as macroeconomics, microeconomics, growth, international economics and others. To provide the students of other fields who will not continue studies on economics, with general, basic insights into economics. Introduction and basic concepts in economics: the subject matter, tools, methods of economics, demand and supply; Introduction to Macroeconomics: National income concepts and accounting, business cycles and economic ailments, determination of national income, aggregate demand and aggregate supply approaches.

Textbook/Recommended Reading :
Economics, Principles, Problems, and Policies, Campbell R. McConnell and Stanley L. Brue, Irwin and McGraw-Hill, Boston, 1999.
Economics Today, Roger LeRoy Miller, Addison-Wesley, Massachusetts, 2000.

Teaching Methods: Lecture/classroom discussions

Assessment tools: Quizzes, midterm exam, final exam

Instruction Language: English


CE 103 Information Technology

Type of Course: Lecture+Lab
Year:1
Semester: Fall
Credits:3 (3+0+0)
Instructor: Dr. Baran Tander

Objective and Contents:
To make the student computer and information literate. Students will be familiar with the concepts of information technology, computer and communication systems, and applications software. Furthermore, they will be able to use office and internet software effectively.History of computers and communications; introduction to computer architecture; computer hardware: I/O, peripherals and storage; operating systems; programming languages; application software: documentation, spreadsheet, presentation; Internet

Textbook/Recommended Reading :
Williams Sawyer and Hutchinson, 2006.
Using Information Technology, McGraw-Hill, New York.

Teaching Methods: Lecture, lab. sessions, office projects

Assessment tools: 1 office project for midterm, take home final exam (web site design)

Instruction Language: English


MA 102 Calculus-II

Type of Course: Lecture+Problem Sessions
Year:1
Semester: Spring
Credits:3 (3+0+0)
Instructor: Prof.Dr. Abdülkadir Özdeğer

Objective and Contents:
The course aims to give the fundamentals of the integral calculus and its applications to various fields. Indefinite integrals. Integration by substitution, Integration by parts. Integration of rational functions, Partial fractions. Trigonometric Substitutions. Definite integrals, Mean Value Theorem for integrals. Fundamental Theorem of the integral calculus. Improper integrals. Some applications of the integral: Length of plane curves, area of plane regions, volumes of solids of revolution, areas of surfaces of revolution.

Textbook/Recommended Reading:
Thomas’s Calculus, 10 th. Ed., Addison - Wesley, 2001.
Calculus, H.Anton, 6 th. Ed., John Wiley, 1999.
Calculus, Tom M. Apostol, Vol.1, Vol.2, Blaisdell pub. Co., New York, 1961.
Schaum’s outline of theory and problems, E.Passow, Mc-Graw-Hill, 1999.

Teaching Methods: Lecturing and problem sessions.

Assessment tools: Homework, two midterm exams and final exam.

Instruction Language: English


SC 102 Statistics

Type of Course: Lecture
Year:1
Semester: Spring
Credits:3 (3+0+0)
Instructor: Assoc. Prof. Dr. Fazıl Güler

Objective and Contents:
Statistics includes inferential statistics which uses numerical summaries to assist in making decisions. Theory of sampling, the sampling distribution of the mean, point and interval estimations, large and small sample, confidence interval for a population mean, t distribution,  confidence interval for a population proportions, small–sample confidence interval for  a population proportions (graphical approach), determining of  sample size. Test of statistical hypotheses, concept of type-I error, large and small sample test of hypothesis about a population mean, large-sample test of hypothesis about a population proportion. Additional tests of hypotheses and confidence interval: Estimating the difference between two populations mean, estimating the difference between two population proportions, a test for the difference between the two population means, a test for the difference between two population proportions.  Simple linear regression and correlation analysis. The OLS method, inference in regression, using the model for prediction, confidence interval for prediction. The Chi-Square distribution, test of independence. The F distribution, analysis of variance.

Textbook/Recommended Reading :
Statistics, J.T. Mc Clave and T. Sincich, 8th. Ed., Prentice Hall, 2000

Teaching Methods: Classroom discussion

Assessment tools: Midterm exam, Final exam

Instruction Language: English


CE 102 Introduction to Computing

Type of Course: Lecture
Year:1
Semester: Spring
Credits:3 (3+0+0)
Instructor: Asst. Prof. Dr. Atilla Özmen

Objective and Contents:
Problem solving, algorithm design and analysis, critical thinking, program implementation of problem definitions and software specifications, basic software debugging. Basic computer systems, the components of typical microcomputer systems, software, hardware, operating system; problem solving, formalization of a solution, computer programs; assembly language, compiler, linker, flowchart, pseudo code; C programming language, input and output operations, variables, declaration of variables, arithmetic and data types, conditional statements; increment and decrement operators; advanced assignment operators, loops, labels and go to, bitwise operators.

Textbook/Recommended Reading
:
C++ How to Program, H.M. Deitel and P.J. Deitel, Prentice-Hall, ISBN 0-13-117334-0, 1994.
Programming with C++, J. R. Hubbard, Schaum’s Outline Series, McGraw-Hill, ISBN 0-07-030837-3, 1996.
A Step-by-Step Guide to C Programming, J.P. Corriveau, Prentice-Hall International, Inc., ISBN 0-13-645896-3, 1998.

Teaching Methods:
Computer Usage: The students will use C++ programming language.

Assessment tools: Two midterm exams, final exam.

Instruction Language: English


EC 132 Economics-II

Type of Course: Lecture
Year:1
Semester: Spring
Credits:3 (3+0+0)
Instructor:Assoc. Prof. Dr. Hüseyin Bilgin

Objective and Contents:
To provide the students of economics, business, and finance with the basic principles, laws and concepts of economics. This course helps build a background for the students who should later master deeper fields of economics such as macroeconomics, microeconomics, growth, international economics and others. To provide the students of other fields who will not continue studies on economics, with general, basic insights into economics. Introduction to microeconomics; The consumer behavior and equilibrium; The theory of production and of costs; The market models; The goods markets: The perfect competition, monopoly, oligopoly, monopolistic competition. The factor markets: land, labor, capital.

Textbook/Recommended Reading :
Economics, Principles, Problems, and Policies,.Campbell R. McConnell and Stanley L. Brue, Irwin and McGraw-Hill, Boston, 1999.
Economics Today, Roger LeRoy Miller, Addison-Wesley, Massachusetts, 2000.

Teaching Methods: Lecture/class discussions

Assessment tools: Quizzes, midterm exam, final exam

Instruction Language: English


TD 122 Türk Dili-II

Type of Course: Lecture
Year:1
Semester: Fall
Credits:3 (3+0+0)
Instructor: Esra Dicle

Objective and Contents:
Öğrencilerin Türkçe’yi doğru ve düzgün biçimde kullanmalarını sağlamak.Türkçe yazımında ifade etme, tanımlama, tartışma ve anlatıma yönelik uygulamalı eğitim; noktalama ve yazımın temel kuralları, örnekler; yazım ve kompozisyon teknikleri; klasik ve çağdaş Türk yazarlarının kitapları; öğrencilerin kompozisyonlarında görülen anlatım bozukluklarının ve noktalama hatalarının düzeltilmesi; rapor, makale gibi bilimsel yazı türlerine örnekler; konferanslarda ve tartışmalarda pratik kazandırmaya yönelik sözlü çalışmalar ve uygulamalar; deneme, şiir, roman, öykü gibi seçilmiş kitapların incelenmesi.

Textbook/Recommended Reading:
Çağdaş Türk Dili, Suer Eker

Teaching Methods: Lecture

Assessment tools: Two midterms, homework, final exam.

Instruction Language: Turkish.


MA 203 Discrete Computational Structures

Type of Course: Lecture
Year:2
Semester: Fall
Credits:3 (3+0+0)
Instructor: Prof. Dr. Alsan Meri

Objective and Contents:
To introduce the fundamentals of discrete mathematics and its applications. Principles of counting, fundamentals of logic, set theory. Properties of integers, mathematical induction. Relations and functions. Principle of inclusion and exclusion, generating functions, recurrence relations. Graph theory, trees, rings and modular arithmetic. Boolean algebra, finite fields, coding theory, Polya’s method of enumeration.

Textbook/Recommended Reading :
Discrete Mathematics and Its Applications, K.H.Rosen, 3 rd. Ed., Mc Graw-Hill, International Ed., Singapore, 1995.

Teaching Methods: Lecturing

Assessment tools: Two Midterm exams, final exam.

Instruction Language: English


CE 241 Programming Languages

Type of Course: Lecture+ Laboratory
Year:2
Semester: Fall
Credits:4 (3+0+2)
Instructor: Asst. Prof. Dr. Atilla Özmen

Objective and Contents:
Analyzing programming language design issues related to data types, expressions, assignment statements and control structures, develop computer code with functions, analyze algorithms or computer code for correctness, identify and correct software faults, analyzing parameter passing methods and classes, analyzing pointers and string, know the relationship between pointers and arrays. Functions, recursive functions, void functions, arguments by value, inline functions, default arguments to a function, function overloading, arrays, 2-D arrays, pointers, arguments by reference, accessing arrays with pointers, passing arrays to functions, strings, accessing strings with pointers, classes.

Textbook/Recommended Reading:
C++ How to Program, H.M. Deitel and P.J. Deitel, Prentice-Hall, ISBN 0-13-117334-0, 1994.
Programming with C++, J. R. Hubbard, Schaum’s Outline Series, McGraw-Hill, ISBN 0-07-030837-3, 1996.
A Step-by-Step Guide to C Programming, J.P. Corriveau, Prentice-Hall International, Inc., ISBN 0-13-645896-3, 1998.

Teaching Methods:
Computer Usage: The students will use C++ programming language.
Laboratory: Two hours per week, hands-on exercises in the computer laboratory.

Assessment tools: Two midterm exams, computer assignments, final exam

Instruction Language: English


IF 221 Introduction to Accounting

Type of Course: Lecture
Year:2
Semester: Fall
Credits:3 (3+0+0)
Instructor: Prof. Dr. Ahmet KIZIL

Objective and Contents:
To teach the accounting to the student as a the art, science and practice concerned with a systematic identifying, collecting, recording, classifying and summarizing in a significant manner and in terms of money, exchange transactions or equivalent economic events of a financial character and interpreting and reporting the results. Definition of accounting, functions of accounting, basic accounting concepts, generally accepted  accounting principles, basic financial statements, accounting books and documents, the accounts, recording and posting, trial balance, end-of-year adjustments, adjusted trial balance, preparing basic financial statements, uniform accounting system.
Textbook/Recommended Reading :
Accounting, Charles T.Horngren, W.T.Harrison, L.S.Bamber, Prentice-Hall International, Inc.,  USA
Accounting and Tax Applications, Ahmet Kızıl, Der Yayınları, Istanbul

Teaching Methods: Classroom Discussion

Assessment tools: Homework, two midterm exams, final exam

Instruction Language: English


BA 221 Introduction to Business

Type of Course: Lecture
Year:2
Semester: Fall
Credits:3 (3+0+0)
Instructor: Assoc. Prof. Dr. Yıldız Y. Güzey

Objective and Contents:
People,Technology and Ethical Behavior, Business Success, Economic Challenges and Globalization,Global Markets,Organizing Small and Large Business,Entrepreneurship,Strategic Management, Management, Leadership, and the Internal Organization, Human Resource Management and Motivation,Customer–Driven Marketing, Goods and Services,Technology and the Internet,Technology and Information, Accounting and Financial Statements

Textbook/Recommended Reading :
Business Today, Stephen P.Robins, Hardcourt, 2001.
The Human side of Enterprise, Douglas McGregor, New York McGraw Hill, 1960

Teaching Methods: Lecture+Case

Assessment tools: One Midterm Exam+Homework+Final Exam

Instruction Language: English


AT 211 Atatürk İlkeleri ve İnkılap Tarihi-I

Type of Course: Lecture
Year:2
Semester: Fall
Credits:2 (2+0+0)
Instructor: Abdülkadir Özçelik

Objective and Contents:
Yakın tarihimiz hakkında öğrencilerin bilgilendirilmesi.Tanzimat Döneminden başlayarak yeni Türkiye Cumhuriyeti’nin kuruluşuna kadar olan önemli olaylar ve Atatürk İlke ve İnkılapları.

Textbook/Recommended Reading:
Türk Devrim Tarihi, Toktamış Ateş, Der Yayınları, 1993

Teaching Methods: Lecture, class discussions

Assessment tools: Midterm exams, final exam

Instruction Language: English

MA 204 Numerical Analysis

Type of Course: Lecture
Year:2
Semester: Spring
Credits:3 (3+0+0)
Instructor: Prof. Dr. Abdülkadir Özdeğer

Objective and Contents:
To introduce the numerical treatments of algebraic and differential equations. Numerical solutions of algebraic equations. Newton-Raphson Method, Iteration Method. Interpolation, extrapolation. Numerical integration. Numerical solutions of ordinary differential equations: Power series solutions.

Textbook/Recommended Reading:
Numerical Methods for mathematics, science and engineering, John H. Mathews, 2 nd. edition, Prentice Hall, 1992 Numerical Analysis, Schaum’s outline series, Francis Scheid, 2nd Ed., McGraw-Hill, 1989

Teaching Methods: Lecturing and problem sessions.

Assessment tools: Homework, two midterm exams and final exam.

Instruction Language: English

 

SC 202  Mathematical Statistics

Type of Course: Lecture+Problem Sessions
Year:2
Semester: Spring
Credits:4 ( 3+2+0)
Instructor: Prof. Dr. Müjgan Tez

Objective and Contents:
Probability distributions, with an emphasis on the mathematical structure. Reviewing point estimation and hypothesis testing, we proceed to more abstract concepts, such as efficiency, consistency, sufficiency. Finally, theorems about optimal estimates and tests are discussed. Probability distributions: a review. The theory of point estimation: review; unbiased estimates; efficiency, consistency, sufficiency; Fisher information; the Cramer-Rao inequality the theory of hypothesis testing: review; the power function; likelihood ratio tests; Neyman-Pearson lemma.

Textbook/Recommended Reading :
An Introduction to Mathematical Statistics and Its Applications, Larsen, Richard J., & Marx, Morris L., Prentice Hall, 2001.
John E. Freund’s Mathematical Statistics, Miller, Irwin, & Miller, Marylees, Prentice Hall, 1999.

Teaching Methods: Classroom discussion, Computer Usage: “R” will be used

Assessment tools: Assignments, term project, final exam

Instruction Language: English


MA 201 Differential Equations

Type of Course: Lecture
Year:2
Semester: Spring
Credits:3 (3+0+0)
Instructor: Prof. Dr. Abdülkadir Özdeğer

Objective and Contents:
To provide a solid understanding of the differential equation concept, problem formulation and solving analysis and critical thinking. Ordinary differential equations. First order and higher order differential equations. General solution, particular solutions and singular solutions. Initial-value and boundary-value problems. Some special kinds of first-order differential equations. Orthogonal trajectories of a one-parameter family of curves. Higher order linear differential equations of constant coefficients. Method of undetermined coefficients and method of variation of parameters. Laplace transforms and their use in solving differential equations. Euler-Cauchy equation. Series solutions of second order differential equations.

Textbook/Recommended Reading :
Differential Equations, S.H. Ross, John Wiley & Sons, 1984.
Ordinary Differential Equations, T. Morris - P. Harry, Harper and Row, New York, 1964.
Elementary Differential Equations and Boundary Value Problems, W.E. Boyce and  R.C. Diprima, John Wiley & Sons Inc. 1977.

Teaching Methods: Lecturing and problem sessions.

Assessment tools: Homework, two midterm exams and final exam.

Instruction Language: English

CE 242 Data Structures and Algorithms

Type of Course: Lecture + Laboratory
Year:2
Semester: Spring
Credits:4 (3+0+2)
Instructor: Dr. Kaya Sarıcalı

Objective and Contents:
o teach how data is arranged in computer’s memory and how computer programs manipulate the stored data. Students will have an understanding of data arrangement and algorithmic approach to the manipulation of data. Java Programming, Object-Oriented Design, Arrays and the Vector class, Recursion, Analysis of Algorithms, Sorting, Collections, Stacks, Queues, Lists, Binary Trees, Heaps and Priority Queues, Graphs.

Textbook/Recommended Reading
Data structures and Algorithm Analysis in C++, M.A. Weiss, Addison-Wesley, 1999. :

Teaching Methods:
Laboratory: Two hours per week, hands-on exercises in the computer laboratory. Each student will carry out the solution of end-of-chapter practices and additional practices supplied by the instructor.
Computer Usage
: The students will use commercial software development platforms employing currently popular programming languages such as Java or C .
Projects/Teamwork: Students are required to develop software packages implementing core algorithms as homework.

Assessment tools: Homework, two midterm exams and final exam.

Instruction Language: English


BA 222 Management and Organization

Type of Course: Lecture
Year:2
Semester: Spring
Credits:3 (3+0+0)
Instructor:Assoc. Prof. Dr. Yıldız Y.Guzey

Objective and Contents:
BA 222 will learn basic Management and Organization topics. Lecturing and problem sessions. The Nature of Management, The environment and Corporate Culture, Ethics and Corporate Social Responsibility, Organizational Goal Setting, Strategy Formulation and Implementation, Managerial Decision Making, Fundamentals of Organizing, Innovation and Change, Human Resource Management, Leadership and Motivation in Organizations, Communication and Teamwork , Control Concepts, Management Control Systems, Information Systems

Textbook/Recommended Reading :
Management, Patrick J. Montana, Bruce H. Charnov, Baron Educational Series Inc., 1993.
The Art of Japanese Management, Richard Tanner Pascale & Anthony, G.Athos, Penguin, 1982.
Two types of bureaucracy:Enabling coercive, Adler, P.&B. Borys, Administrative Science Quarterly, 61-89, 1996.
Bringing together the old and New Institutionalism, Academy of      Management Review, 21(4)1022-1054

Teaching Methods: Case, Class discussion

Assessment tools: Midterm, Homework, Final Exam

Instruction Language: English


AT 212 Atatürk İlkeleri ve İnkılap Tarihi-II

Type of Course: Lecture
Year:2
Semester: Spring
Credits:2 (2+0+0)
Instructor: Abdülkadir Özçelik

Objective and Contents: Yakın tarihimiz hakkında öğrencilerin bilgilendirilmesi.Kurtuluş ve Kuruluş başlıkları altında İstiklal Savaşı, bütün önemli olaylar, Cumhuriyeti’in ilanından başlayarak çeşitli alanlarda gerçekleştirilen reformlar.

Textbook/Recommended Reading:
Türk Devrim Tarihi, Toktamış Ateş, Der Yayınları, 1993.

Teaching Methods: Lecture, class discussions

Assessment tools: Midterm exams, final exam

Instruction Language: English


SC 301 Non-Parametric Statistical Methods

Type of Course: Lecture
Year:3
Semester: Fall
Credits:3 (3+0+0)
Instructor: Prof. Dr. Gülay Kıroğlu

Objective and Contents:
The objective of this course is to present the advantages and disadvantages of non- parametric methods and to give the basic techniques of non-parametric statistical methods and its applications to various fields. Advantages and disadvantages of non-parametric methods, permutation tests, the sign test, the sign test for trend, the signed-rant test, The Wilcoxon signed rank test, robustness, matching samples to distributions-Kolmogorov’s test, Run test, rank-sum tests, the U test, the H test, methods for paired samples, the median test, The Wilcoxon - Mann - Whitney test, The Siegel-Tukey test, correlation and concordance, The Kendall rank correlation coefficient, Spearman’s rank correlation coefficient, regression, Theil’s regression method, categorical data.

Textbook/Recommended Reading :
Non-parametric Statistical Methods, M. Hollander and A.Dauglas, 2nd Ed., New York, 2001.
Non-parametrics Statistical Methods Based on Ranks, L. Lehman, Mc Graw-Hill, 1985.
Non-parametrics and Time series, S. Ghos, New York, 2000.
Handbook of Parametric and Non parametric Statistical Procedures, J. Sheskin, D. Sheskin, 2nd Ed., 1997.
Applied Non-Parametric Statistical Methods, R.Sprend, 2nd Ed., Chapman & Hall, London, 1993.
An Introduction to Modern Non-parametric Statistic ,J.Higgins, 1998.

Teaching Methods:
Computer Usage: The students will use SPSS for their work.
Projects/Teamwork: Students will complete all performance requirements prepare a project about different subject and then will present and discuss them with other students and instructor.

Assessment tools: One midterm exam, term project, final exam

Instruction Language: English


SC 303 Sampling Theory

Type of Course: Lecture
Year:3
Semester: Fall
Credits:3 (3+0+0)
Instructor: Assoc. Prof. Dr. Fazıl Güler

Objective and Contents:
This course includes how to design a sampling plan for collecting data from population based on different sampling techniques and how to analyze it. Review of basic statistical concepts, elements of sampling problems, simple random sampling, stratified random sampling, cluster sampling, systematic sampling.
Designing of data collection, applied field operations, analysis and reporting of field operation results.

Textbook/Recommended Reading :
Sampling: Design and Analysis., S. Lohr., Duxbury Press, 1999
Sampling Theory, T. Yamane., Prentice Hall,1967
Marketing Research An Applied Approach, Kinnear, T.C., Taylor, J.C., McGraw Hill, 1991.

Teaching Methods: Classroom discussion

Assessment tools: Midterm exam, Final exam

Instruction Language: English


CE 341 Operating Systems

Type of Course: Lecture
Year:3
Semester: Fall
Credits:3 (3+0+0)
Instructor: Ataman Yıldırım

Objective and Contents:
The course presents the concepts, design, structure and mechanisms of general operating systems. Different kinds of computer systems are analyzed from single user to multi-users, from primitive ones to contemporary ones. Future directions in operating systems are introduced. Consequently, the course provides the design trade-offs between hardware, software and all kind of resources for the student. Operating System, history of OS; open systems; general mechanisms; interrupt, registers, buffering, semaphore, deadlock, resource management; process management, memory management, device management,  information management, UNIX; kernel, shell.

Textbook/Recommended Reading:
Classroom Discussion
Projects/Teamwork:
Teams of students (2-3 students per team) prepares papers on virtual memory or process management or LINUX.

Teaching Methods: Lecturing

Assessment tools: Homework, two-three quizzes, two midterm exams, term project, final exam

Instruction Language: English


CE 343 Object Oriented Programming Languages

Type of Course: Lecture
Year:3
Semester: Fall
Credits:3 (3+0+0)
Instructor: Dr. Kaya Sarıcal

Objective and Contents:
To teach object oriented approach for computer program development using Java language. Students will have an understanding of programming logic, object oriented approach and Java language. Programming and Software Design, Object Orientation and Java, IDE, Java Language Basics, Introduction to Applets, Data Types in Java, Strings and Characters, Classes and Objects, Methods, Control Structures, GUI Components, Arrays, Inheritance, Exception Handling, Database Connectivity.

Textbook/Recommended Reading:
Java: An Object Oriented Language, M. Smith, McGraw-Hill Publishing Company, London, 2002.
Java: How To Program 3 Ed., Deitel and Deitel, Prentice Hall, New Jersey.
Java with Visual J++, D.W. Gill, CRC Press, Florida, 2000.


Teaching Methods:
Computer Usage:
The students must install Java Development Kit (JDK 1.5.x) and NetBeans IDE (5.x) to compile and run programs which will be provided to them as part of the course support material.
Project: Students, either individually or in a team of 2, will submit term assignments, modelling real life situations, objects and their behaviors, involving object-oriented design, GUI and database connectivity.

Assessment tools: Midterm exam, term project, final exam.

Instruction Language: English


SC 302 Decision Theory

Type of Course: Lecture
Year:3
Semester: Spring
Credits:3 (3+0+0)
Instructor: Prof. Dr. Nalan Cinemre

Objective and Contents:
Decision theory is concerned with rational decisions under uncertainty. The aim of this lecture is to provide an introduction to the models of decision theory and to illustrate them with many examples. It is shown how decision theory is related to, and actually provides the theoretical basis for, classical statistical problems such as parameter estimation and hypothesis testing. A chapter on game theory concludes the lecture. What is decision theory? Theoretical questions about decisions, normative and descriptive theories; decision making; the standard representation of individual decisions: Alternatives, decision matrices, decision trees; decision theories: Decision under certainty, decision under uncertainty, decision under risk; expected utility: What is expected utility?, objective and subjective utility, appraisal of expected utility, probability estimates; Bayesian decision theory.

Textbook/Recommended Reading :
Statistical Decision Theory and Bayesian Analysis, Berger, James O., Springer Verlag, 1993.
Elementary Decision Theory, Chernoff, Herman, & Moses, Lincoln E. Dover Publications, 1987.
A Primer in Game Theory, Gibbons, Robert, Prentice Hall.
Applied Statistical Decision Theory, Raiffa, Howard, & Schlaifer, Robert,  Wiley, 2000.

Teaching Methods: Classroom discussion

Assessment tools: Midterm exam, final exam

Instruction Language: English


SC 304 Multivariate Statistical Analysis

Type of Course: Lecture
Year:3
Semester: Spring
Credits:3 (3+0+0)
Instructor: Prof. Dr. Gülay Kıroğlu

Objective and Contents:
The goal of this course is to provide students with knowledge necessary to make proper interpretations and select appropriate techniques for analyzing multivariate data.Aspects of multivariate analysis, Comparisons of several multivariate means, principal components analysis, factor analysis, canonical correlation analysis, discriminate analysis, cluster analysis.

Textbook/Recommended Reading :
Applied Multivariate Statistical Analysis, R.A. Johnson, D.W. Wichern,  5th ed., Prentice Hall, 2002

Teaching Methods: Class discussion and applications with using computer

Assessment tools: Midterm exam, Final exam

Instruction Language: English


CE 344 Database Management Systems

Type of Course: Lecture + Laboratory
Year:3
Semester: Spring
Credits:4 (3+0+2)
Instructor: Asst. Prof. Dr. Arif Selçuk Öğrenci

Objective and Contents:
To provide a solid understanding of RDBMS (Relational Database Management Systems). The students will be able to carry out analysis, design, and implementation in the development of a RDBMS. Data modeling; E-R diagrams; conceptual, logical and physical database design; constraint modeling; database management systems; database architectures; Oracle as a relational database management system; SQL: selection, DML, DCL DDL operations; PL/SQL; construction of program units using PL/SQL; integration of PL/SQL units with ORACLE.

Textbook/Recommended Reading:
Introduction to Oracle: SQL and PL/SQL, Oracle course book.
Develop PL/SQL Program Units, Oracle course book.
Database systems: a practical approach to design, implemen­tation, and management, T. M. Connolly and C. E. Begg.
An introduction to database systems, C.J. Date.
Oracle8i: A Beginner's Guide, M. Abbey, I. Abramson and M. J. Corey,.

Teaching Methods:
Laboratory: Two hours per week, hands-on exercises in the computer laboratory. Each student will carry out the solution of end-of-chapter practices and additional practices supplied by the instructor.
Computer Usage: The students will use Oracle Server, Oracle SQL Plus, and Procedure Builder environments for exercising SQL and PL/SQL.
Projects/Teamwork: Teams of students (3-4 students per team) will compete for designing and implementing the “best” database management system satisfying the requirements/constraints supplied by the instructor (or by a real customer) for a real life business case.

Assessment tools: Homework, two midterms, term project, final exam

Instruction Language: English

SC 401 Time Series Analysis I

Type of Course: Lecture
Year:4
Semester: Fall
Credits:3 (3+0+0)
Instructor: Asst. Prof. Dr. Füsun Deriş

Objective and Contents:
The goal of this course is to provide students the knowledge of time series techniques and their application to the analysis and forecasting of time series. Introduction to time series analysis, smoothing methods, decomposition methods, linear time series models and ARIMA modeling.  

Textbook/Recommended Reading :
Introduction to Time Series Analysis and Forecasting with Applications of SAS and SPSS, R.A. Yafee, M. Macgee, Academic Press, 2000.

Teaching Methods:
Computer Usage: Applications by using EViews 4.1/5.0 programms with computer.

Assessment tools: Midterm exams, final exam

Instruction Language: English


SC 403 Operations Research

Type of Course: Lecture
Year:4
Semester: Fall
Credits:3 (3+0+0)
Instructor:

Objective and Contents:
To decide how to make the most effective use of an organization’s resources. To provide each student with the tools required in understanding, analyzing, modeling complex problems in the real world. Introduction to linear programming; construction of the LP model, graphical LP solution; the simplex method;  the M-Method, the two-phase method; duality and sensitivity analysis; the transportation and assignment problems; hungarian algorithm, Modi method, Vogel’s approximation method.

Textbook/Recommended Reading:
Yöneylem Araştırması, N. Cinemre, 2. baskı, Beta, 2004.
Operations Management, theory and problems, J.G. Monks, 2nd ed., Mc-Graw Hill, 1982.
Operations Research Applications and Algorithms, W.L. Wayne, 2nd ed., PWS Pub. Co.,  1991.

Teaching Methods:
Classroom discussion
Computer Usage: The students will use Tora for problem solving.

Assessment tools: Homework, attendance, two midterm exams, final exam.

Instruction Language: English


IF 323 Financial Analysis

Type of Course: Lecture
Year:4
Semester: Fall
Credits:3 (3+0+0)
Instructor: Dr. Öztin Akgüç

Objective and Contents:
To make the student acquainted and introduced with the basic financial problems of modern corporations. The students will acquire the basics of corporate finance and will be familiar with financial concepts. Scope of Financial Analysis, Basic Financial Statements ( Balance Sheet, Income Statement, Statement of Retained Earnings, Statement of Source and Use of Working Capital, Statement of Changes in Net Worth, Statement of Sources and Uses of Funds (Statement of Flow of Fonds), Statement of Cash Flow ), Relationships Among The Financial Statements, Techniques (Methods) of Financial Statement Analysis (Comparative Statement Analysis, Vertical Percantage Analysis, Trend Analysis, Ratio Analysis, Liquidity Ratios, Financial Structure Ratios (Leverage Ratios), Activity Ratios (Turnover Ratios), Profitability Ratios), Du Pont System of Financial Analysis, Break-even Analysis.

Textbook/Recommended Reading:
Weston J. Fred, Brigham F. Eugene. Managerial Finance

Teaching Methods: Lecture/Classroom discussion

Assessment tools: Quizzes, Midterm and Final Exams

Instruction Language: English


SC 402 Time Series Analysis II

Type of Course: Lecture
Year:4
Semester: Spring
Credits:3 (3+0+0)
Instructor: Asst. Prof. Dr. Füsun Deriş

Objective and Contents:
The goal of this course is to provide students the knowledge of advanced  time series techniques and  their application to the analysis and forecasting of time series. Alternative unit root tests, model and lag specification in seasonal series and forecasting, heteroskedasticity/modeling variance, cointegration and testing presence, view of multivariate time series analysis and vector autoregressive(VAR) models.

Textbook/Recommended Reading :
Analysis of Financial Time Series, S. Ruey, Tsay, John-Wiley&Sons, 2002.
Quantitative Forecasting Methods, N.R. Farnum and L.W. Standon John Wiley and Sons, Boston, PWS-Kent, 1989.

Teaching Methods:
Computer Usage: Applications by using EViews 4.1/5.0 programms with computer.

Assessment tools: Midterm exams, final exam

Instruction Language: English


SC 404 Stochastic Processes

Type of Course: Lecture
Year:4
Semester: Spring
Credits:3 (3+0+0)
Instructor: Staff

Objective and Contents:
A nonmeasure theoretic introduction to stochastic processes. The knowledge of its diverse range of applications and with probabilistic intuition and insight in thinking about problems. Markov chains, birth and death processes; queuing chains; stationary distributions of a Markov chain; reducible chains; Markov pure jump processes; second order processes; continuity, integration and differentiation o second order processes; stochastic differential equations, estimation theory, and spectral distributions.

Textbook/Recommended Reading :
Stochastic Processes, Sheldon M. Ross, 2nd Ed., Wiley, 1995.
Introduction to Stochastic Processes, P.G. Hoel, S.C.

Teaching Methods: Classroom discussion and applications by using computer

Assessment tools: Midterm exams, final exam

Instruction Language: English


SC 400 Project

Type of Course: Lecture
Year:4
Semester: Spring
Credits:3 (3+0+0)
Instructor: Spring

Objective and Contents:
Students will be prepared project in field of statistics or computer sciences


Technical Electives

IE 331 Management Information Systems

Type of Course: Lecture
Year:3
Semester: Fall
Credits:3 (3+0+0)
Instructor: Assoc. Prof. Dr. Yıldız Güzey

Objective and Contents:
The overall objective of this course is to introduce and explore issues to Management Information Systems. Information systems and the organization. Importance of timely, accurate and relevant information for decision making. Levels of management and information needs. Integration and coordination of individual business information systems.

Textbook/Recommended Reading :
Management Information Systems, G.V. Post and D.L. Anderson, 4th Ed., McGraw-Hill/Irwin, 2006, ISBN: 0-07-111638-9

Teaching Methods:Lecture, class discussions, case studies

Assessment tools: Midterm exams, quizes, homework, attendance, final exam

Instruction Language: English


CE 349 Formal Languages and Automata Theory

Type of Course: Lecture
Year:3
Semester: Fall
Credits:3 (3+0+0)
Instructor: Dr. Habib Şenol

Objective and Contents:
This course includes knowledge of basic theoretical results of computability, and an understanding of various kinds of abstract machines and what problems they solve. Moreover, it is an introduction to theory of computation providing a perspective on computer science as a discipline. Basic mathematical representation techniques; regular expressions and regular languages; finite state machines with output, deterministic finite automata, non-deterministic finite automata; grammar definitions; context-free languages; push-down automata.

Textbook/Recommended Reading :
Formal Diller ve Soyut Makineler, Z. Altan, Istanbul University Publications, 2001.
J.E. Hopcroft and J.D. Ullman, Introduction To Automata Theory, Addison-Wesley.
http://www.cs.duke.edu/~rodger/tools/jflap/

Teaching Methods: Lecture, class discussions, case studies

Assessment tools: Two midterm exams, homework, attendance, final exam

Instruction Language: English


CE 354 Embedded System Design

Type of Course: Lecture
Year:3
Semester: Spring
Credits:3 (3+0+0)
Instructor: Asst. Prof. Dr. Osman Kaan Erol

Objective and Contents:
The course provides advanced knowledge in the design of complex computer systems, in particular embedded systems. Models and methods are discussed that are fundamental for systems that consist of software and hardware components. Embedded Systems Overview, Embedded System Components, Electronic Design Aid Tools, Printed Circuit Board Design Techniques, Summary and Future Vision

Textbook/Recommended Reading :
EDN Europe
EPN
Atmel, Philips 8051 Family Microncontrollers Data Books
TI MSP430 Application Notes.
PIC 12Cxxx Series Microntrollers Data Book.
Maxim/Dallas Application notes
Cypress PSoC DataBook

Teaching Methods: Lecture, class discussions, case studies

Assessment tools: Project, quizzes, final exam

Instruction Language: English


SC 308 Network Operating Systems

Type of Course: Lecture
Year:3
Semester: Spring
Credits:3 (3+0+0)
Instructor: Ataman Yıldırım

Objective and Contents:
The course presents structure and mechanisms of general multi-user operating systems, specially open UNIX operating systems and gives information about knowledge. The student will gain hands-on skills on multi-user UNIX systems. Open system, kernel, shell, UNIX: commands, directory structure, editor vi; servers and clients, installation; software package and patch administration; managing user accounts and groups; user’s work environment; managing system security, File security; shutting down and booting a system; run levels; device and disk management; file systems, swap space, checking file system integrity; backing up and restoring data; printer management.

Textbook/Recommended Reading:
UNIX Operating System, A. Yıldırım, unpublished lecture notes.
Sun Solaris 2.X System Administration
Operating Systems, S.E. Madnick and J.J. Donovan.
Operating Systems, W. Stallings.
Operating Systems, A.S.Tanenbaum and A.S. Woodhool.

Teaching Methods:
Computer Usage: SUN server and SUN clients are used for practice.

Assessment tools: Homework, two-three quizzes, two midterm exams, final exam

Instruction Language: English


SC 407 Methods of Qualitative Research

Type of Course: Lecture
Year:4
Semester: Fall
Credits:3 (3+0+0)
Instructor: Ayşe Mutaf

Objective and Contents:
This course serves as an introduction to the practices and methods of qualitative research. We will exercise our curiosity and intellect as we explore the qualitative field through readings, discussions, lectures, and media works. The course sets the stage for students to deepen their understanding of theoretical, conceptual, interpretive, representational, and fieldwork practices, as well as to explore the fundamental questions related to who they are as researchers. Introduction to qualitative research: What is qualitative research, advantages and disadvantages of qualitative research, usage areas. Psychological processes that influences behavior and their relationship to qualitative research. Methods used in qualitative techniques used in qualitative research: Group discussions, in depth interviews, observation/Ethnographic studies, projective techniques used in qualitative research.
For each of the methods indicated above, the following points will be discussed: Usage areas, choice of the sample and recruitment (factors to be considered, such as demographic and socio-economic classes, specific characteristics of the sample, recruitment questionnaire and approach, etc.), preparation of the discussion/interview flow, moderation/observation criteria, tape recording, video recording, ethics. Evaluation of the data and writing a report.

Textbook/Recommended Reading :
Developing Focus Group Research, Politics, Theory and Practice, Sage Pub., Rosaline Barbour, Jenny Kitzinger, 1999.
The landscape of qualitative research, theories and issues, Sage Pub., London, 1998.
The quality of Qualitative Research, Sage Pub., London, 1999.
Qualitative Research & Evaluation Methods, Michael Quinn Patton (3rd ed.), Sage Pub., 2001.
Qualitative Research : Theory, Method and Practice, David Silverman (2nd ed.) Sage Pub., 2004.

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