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Applied Mathematics and Statistics Program at Izmir University of Economics offers a comprehensive curriculum designed to equip students with the essential mathematical, statistical, and analytical skills necessary for solving real-world problems across various industries. The program emphasizes both theoretical foundations and practical applications, preparing graduates for diverse careers in data analysis, financial modeling, research, and technology fields.
Students in this program will engage with core mathematics courses such as calculus, linear algebra, differential equations, and discrete mathematics, providing a solid base for advanced studies. In addition, the curriculum includes specialized courses in statistics, probability theory, stochastic processes, regression analysis, multivariate statistics, and statistical computing, ensuring a thorough understanding of data analysis techniques. The program also offers coursework in computational mathematics, programming, and data management, enabling students to handle large datasets and utilize modern analytical software.
The interdisciplinary nature of Applied Mathematics and Statistics aims to develop students' problem-solving skills, quantitative reasoning, and critical thinking abilities. Through various laboratory sessions, projects, and internships, students gain hands-on experience in data collection, modeling, simulation, and interpretation. The program collaborates with industry partners and research institutions, providing students with opportunities for practical training and research activities that enhance employability and professional development.
Graduates of the Applied Mathematics and Statistics program are well-prepared for careers in finance, insurance, healthcare, information technology, government agencies, and research organizations. They may pursue roles such as data analyst, statistician, operational researcher, financial analyst, or further academic study at the postgraduate level. The program also fosters entrepreneurial thinking and innovation, encouraging students to develop solutions to complex problems through mathematical modeling and statistical analysis.
Our faculty comprises experienced academics and industry experts committed to delivering high-quality education and supporting students in achieving their academic and professional goals. State-of-the-art facilities, modern laboratories, and a vibrant academic community create an ideal environment for learning and research. The program emphasizes internationalization and offers opportunities for student exchange and collaboration with global partners, preparing students for effective participation in a global job market.
By choosing the Applied Mathematics and Statistics program at Izmir University of Economics, students embark on a challenging yet rewarding academic journey that combines theoretical insight with practical expertise, opening doors to a wide array of professional opportunities in today's data-driven world.
To see the course details (such as objectives, learning outcomes, content, assessment and ECTS workload), click the relevant Course Code given in the table below.
1. Year Fall Semester | ||||||
Code | Pre. | Course Name | Theory | Application/Laboratory | Local Credits | ECTS |
ELEC 001 | Elective Course I | 3 | 0 | 3 | 7.5 | |
MATH 505 | Advanced Mathematical Analysis | 3 | 0 | 3 | 7.5 | |
MATH 601 | Differential Equations | 3 | 0 | 3 | 7.5 | |
STAT 601 | Probability Theory and Mathematical Statistics | 3 | 0 | 3 | 7.5 | |
Total : | 30 |
1. Year Spring Semester | ||||||
Code | Pre. | Course Name | Theory | Application/Laboratory | Local Credits | ECTS |
ELEC 002 | Elective Course II | 3 | 0 | 3 | 7.5 | |
ELEC 003 | Elective Course III | 3 | 0 | 3 | 7.5 | |
GSNS 695 | Seminar | 0 | 0 | 0 | 7.5 | |
MATH 602 | Advanced Linear Algebra and Optimization | 3 | 0 | 3 | 7.5 | |
Total : | 30 |
2. Year Fall Semester | ||||||
Code | Pre. | Course Name | Theory | Application/Laboratory | Local Credits | ECTS |
GSNS 697 | Individual Studies in Applied Mathematics and Statistics | 0 | 0 | 0 | 30 | |
Total : | 30 |
2. Year Spring Semester | ||||||
Code | Pre. | Course Name | Theory | Application/Laboratory | Local Credits | ECTS |
GSNS 698 | Thesis Proposal in Applied Mathematics and Statistics | 0 | 0 | 0 | 30 | |
Total : | 30 |
3. Year Fall Semester | ||||||
Code | Pre. | Course Name | Theory | Application/Laboratory | Local Credits | ECTS |
GSNS 699 | Thesis | 0 | 0 | 0 | 30 | |
Total : | 30 |
3. Year Spring Semester | ||||||
Code | Pre. | Course Name | Theory | Application/Laboratory | Local Credits | ECTS |
GSNS 699 | Thesis | 0 | 0 | 0 | 30 | |
Total : | 30 |
4. Year Fall Semester | ||||||
Code | Pre. | Course Name | Theory | Application/Laboratory | Local Credits | ECTS |
GSNS 699 | Thesis | 0 | 0 | 0 | 30 | |
Total : | 30 |
4. Year Spring Semester | ||||||
Code | Pre. | Course Name | Theory | Application/Laboratory | Local Credits | ECTS |
GSNS 699 | Thesis | 0 | 0 | 0 | 30 | |
Total : | 30 |
Elective Courses | ||||||
Code | Pre. | Course Name | Theory | Application/Laboratory | Local Credits | ECTS |
ECON 517 | Financial Econometrics | 3 | 0 | 3 | 7.5 | |
FM 506 | Stochastic Processes in Finance | 3 | 0 | 3 | 7.5 | |
IE 502 | Probabilistic Systems Analysis | 3 | 0 | 3 | 7.5 | |
IES 503 | Artificial Intelligence | 3 | 0 | 3 | 7.5 | |
IES 508 | System Simulation and Modeling | 3 | 0 | 3 | 7.5 | |
IES 509 | Heuristics | 3 | 0 | 3 | 7.5 | |
IES 511 | Machine Learning | 3 | 0 | 3 | 7.5 | |
IES 513 | Mathematical Programming and Applications | 3 | 0 | 3 | 7.5 | |
IES 534 | Nonlinear Programming | 3 | 0 | 3 | 7.5 | |
IES 570 | Criptology and Computer Security | 3 | 0 | 3 | 7.5 | |
MATH 504 | Statistics | 3 | 0 | 3 | 7.5 | |
MATH 508 | Partial Differential Equations | 3 | 0 | 3 | 7.5 | |
MATH 552 | Copula Theory and Its Application in Finance | 3 | 0 | 3 | 7.5 | |
MATH 553 | Optimization | 3 | 0 | 3 | 7.5 | |
MATH 554 | Basic Topics in Mathematics | 3 | 0 | 3 | 7.5 | |
MATH 555 | Financial Mathematics | 3 | 0 | 3 | 7.5 | |
MATH 600 | Mathematics Softwares and Research Methods | 3 | 0 | 3 | 7.5 | |
MATH 654 | Discrete Optimization and Heuristic Methods | 3 | 0 | 3 | 7.5 | |
MATH 655 | Fuzzy Set Theory and Its Applications | 3 | 0 | 3 | 7.5 | |
MATH 656 | Complex Analysis | 3 | 0 | 3 | 7.5 | |
MATH 657 | Time Scales | 3 | 0 | 3 | 7.5 | |
MATH 658 | Data Analysis with Mathematica | 3 | 0 | 3 | 7.5 | |
MATH 659 | Graph Theory | 3 | 0 | 3 | 7.5 | |
MATH 660 | Algebraic Geometry | 3 | 0 | 3 | 7.5 | |
MATH 661 | Finite Fields and Its Applications | 3 | 0 | 3 | 7.5 | |
MATH 662 | Cryptography | 3 | 0 | 3 | 7.5 | |
MATH 663 | Biomathematics | 3 | 0 | 3 | 7.5 | |
MATH 664 | Invariant Theory | 3 | 0 | 3 | 7.5 | |
MATH 665 | Algebraic Coding Theory | 3 | 0 | 3 | 7.5 | |
MATH 666 | Integral Equations | 3 | 0 | 3 | 7.5 | |
MATH 667 | Theory of Finite Elements | 3 | 0 | 3 | 7.5 | |
MATH 668 | Spectral Analysis of Differential Operators | 3 | 0 | 3 | 7.5 | |
MATH 669 | Applied Homology, Computational Approach | 3 | 0 | 3 | 7.5 | |
MATH 670 | Set Theoretic Topology | 3 | 0 | 3 | 7.5 | |
MATH 671 | Fuzzy Optimization | 3 | 0 | 3 | 7.5 | |
MATH 672 | Algebra | 3 | 0 | 3 | 7.5 | |
MATH 673 | Computational Commutative Algebra | 3 | 0 | 3 | 7.5 | |
MATH 674 | Group Theory and Its Applications | 3 | 0 | 3 | 7.5 | |
MATH 675 | Applications of Modules and Representation Theory | 3 | 0 | 3 | 7.5 | |
STAT 501 | Theory of Statistics | 3 | 0 | 3 | 7.5 | |
STAT 502 | Stochastic Processes | 3 | 0 | 3 | 7.5 | |
STAT 503 | Probability Theory | 3 | 0 | 3 | 7.5 | |
STAT 504 | Nonparametric Statistics | 3 | 0 | 3 | 7.5 | |
STAT 505 | Applied Statistical Analysis | 3 | 0 | 3 | 7.5 | |
STAT 506 | Multivariate Statistics and the Theory of Copulas | 3 | 0 | 3 | 7.5 | |
STAT 551 | Actuaria | 3 | 0 | 3 | 7.5 | |
STAT 552 | Ordered Random Variables | 3 | 0 | 3 | 7.5 | |
STAT 553 | Reliability | 3 | 0 | 3 | 7.5 | |
STAT 554 | Statistical Process Control | 3 | 0 | 3 | 7.5 | |
STAT 555 | Risk Analysis | 3 | 0 | 3 | 7.5 | |
STAT 556 | Linear Statistical Models | 3 | 0 | 3 | 7.5 | |
STAT 557 | Time Series Analysis | 3 | 0 | 3 | 7.5 | |
STAT 558 | Design of Experiment | 3 | 0 | 3 | 7.5 | |
STAT 559 | Advanced Probability Theory | 3 | 0 | 3 | 7.5 | |
STAT 560 | Statistical Methods in Biology and Medical Sciences | 3 | 0 | 3 | 7.5 | |
STAT 561 | Statistical Softwares and Simulation | 3 | 0 | 3 | 7.5 | |
STAT 562 | Combinatorial Analysis and Discrete Distributions | 3 | 0 | 3 | 7.5 | |
STAT 563 | Statistical Decision Theory | 3 | 0 | 3 | 7.5 |
The students studying in this Ph.D program are required:
Take at least 7 courses with 21 local credits (Master degree holders),
Take at least 14 courses with 42 local credits (Undergraduate degree holders),
Take 240 ECTS and obtain a GPA of 3.00 over 4.00 (Master degree holders),
Take 300 ECTS and obtain a GPA of 3.00 over 4.00 (Undergraduate degree holders),
Pass the proficiency exam,
Succeed in thesis proposal and thesis exam,
Prepare and defend a doctoral thesis,
Score at least CC/S in all the master program courses required by the program, and at least CB/S in all the doctoral program courses.
B-2- FOREIGN NATIONALS:
To hold an Undergraduate or Master Degree with Thesis Diploma (Students, who enrolled to non-thesis master programs before February 06, 2013, are not required to hold “Master Degree with Thesis Diploma”.),
To graduate from undergraduate program (4 year) of Departments of Mathematics, Statistics, Chemistry, Biology, or Physics, Mathematical Engineering, Computer Engineering, Software Engineering, Industrial Engineering, Industrial Systems Engineering, Electrical Electronics Education, Economics, Logistics Management, Finance, or Financial Mathematics to apply for Applied Mathematics or Statistics master program,
To obtain the scores in the exams specified below, or obtain an equivalent score in the internationally recognized foreign language exams that are deemed equivalent to the exams specified below by the Higher Education Board,
Type of Exam |
Score |
KPDS ( Public Personnel Language Exam ) |
70* |
UDS ( Interuniversity Foreign Language Exam ) |
70* |
YDS (Foreign Language Placement Exam) |
70 * |
The Financing studies for the Applied Mathematics and Statistics program at Izmir University of Economics are designed to provide students with comprehensive information regarding the various financial aspects involved in pursuing this degree. The program generally offers a range of funding options to support students throughout their academic journey. These may include scholarships based on academic performance, financial need, or specific criteria such as talents or extracurricular achievements. The university's scholarship programs are integral to attracting talented students and ensuring accessible education. Additionally, students might have the opportunity to participate in teaching or research assistantship roles, which not only provide financial support but also enhance their academic experience and professional development.
Tuition fees for the program are set annually and are publicly available on the university's official website. The fees are competitive relative to similar programs within Turkey and are structured to reflect the level of education and resources provided. The university may also offer installment payment options to ease financial burdens. International students, if applicable, should inquire specifically about any additional fees or funding opportunities available to them. Beyond university-based funding, students might qualify for external scholarships and grants offered by governmental agencies, private foundations, or international organizations, which can substantially reduce the overall cost of education.
Students are encouraged to actively seek financial aid early in their academic planning and to contact the university's student affairs or financial aid office for personalized guidance. The university provides resources and assistance to help students identify appropriate funding options, complete application procedures, and meet deadlines. Moreover, some students may qualify for student loans or other financial arrangements through external entities. It is crucial for prospective and current students to regularly check official university communications and the financial aid section of the Izmir University of Economics website for the most accurate and updated information regarding available financing studies, eligibility criteria, application processes, and deadlines related to the Applied Mathematics and Statistics program.
Applied Mathematics and Statistics program at Izmir University of Economics offers a comprehensive curriculum designed to equip students with strong mathematical and statistical skills applicable in various industries. The program emphasizes both theoretical foundations and practical applications, ensuring graduates are well-prepared for careers in data analysis, finance, research, and technology sectors. Students gain expertise in areas such as differential equations, probability theory, statistical inference, data modeling, and computational methods. The curriculum includes coursework in advanced mathematics, programming languages like R and Python, and data management techniques, fostering analytical thinking and problem-solving abilities.
The program is structured to promote hands-on experience through projects, internships, and collaborations with industry partners, enabling students to apply their knowledge to real-world challenges. Faculty members are experienced professionals and researchers who guide students through contemporary topics like machine learning, artificial intelligence, and big data analytics. Additionally, the program encourages participation in seminars, workshops, and research activities to enhance learning and professional development.
Graduates of the Applied Mathematics and Statistics program are prepared for diverse career paths including data analyst, quantitative researcher, operations analyst, and statistical consultant. They can also pursue postgraduate studies to deepen their expertise in specialized fields or engage in academic research. The university provides state-of-the-art facilities and a supportive learning environment to foster innovation and academic excellence. Overall, this program aims to cultivate highly skilled professionals capable of leveraging mathematical and statistical tools to solve complex problems across various domains, contributing both to technological advancement and economic growth.