STAT 101 Probability and Statistics I (4,0,0)4:Random event sets and classes, sigma algebra, probability measure and probability space, some particular probability problems, conditional probability, Bayes rule, independence of events, random experiment, sample spaces and events, Modeling random experiments, random variables, distribution function, probability function, expected value and variance, moment generating function, uniform, Bernoulli, binomial, geometric, negative binomial and hypergeometric distributions and their places of usage as model.

STAT 102 Probability and Statistics II (4,0,0)4: Continuous random variables and probability density functions, expected value and variance, moment generating function, transformations of random variables, uniform, exponential and normal distributions and their places of usage as model, description of observations, estimation and test concepts, statistical decision concepts.

STAT 105 Computer Programming I (2,2,0)3: Computer hardware, operating system, software, use of computers for statistical applications and their principles, introduction to information systems, introduction to global networks.

STAT 106 Computer Programming II (2,2,0)3: The logic of algorithm and a current generation BASIC programming language, informations about numerical calculations, introduction to structural programming concepts and methods, global networks and web design.

MATH 101 Calculus I (4,2,0)5: Numbers and functions, graphics and curves, trigonometric functions, exponential and logarithmic functions, hyperbolic functions, series and sequences, power sequences, Taylor and MacLauren sequences, Binomial theorem, convergence and divergence, differentiation, applications of differentiation, extreme values, mean value theorem, Rolle Theorem, law of L’Hospital, uncertainty limits, differential and approximate calculations, definite and indefinite integrals.

MATH 102 Calculus II (4,2,0)5: Integral tecniques, integral applications, limit calculation with the aid of integral, serial expansion of functions, Taylor expansion, multivariate functions, partial differentiations, maximum and minumum for multivariate functions, Lagrange multipliers, differential operation under integral notation, multiple integrals, curves in three dimensional space, curvilinear integrals, vector objects, Gren and Stokes theorems.

MATH 113 Linear Algebra I (2,2,0)3: Vector space concept, vectors in a plane, vectors in space, sub-vector space, linear dependence and independence of a vector set, properties belong to vector space basis, dimensions of sub-spaces, direct total, total space and intersection space, inner product, inner product spaces, orthonormal vector systems, method of Gram-Schmidt, sub-spaces of inner product spaces, orthogonal complement, linear transformations, kernel of a linear transformation and rank of a linear transformation, matrix and matrix spaces.

MATH 114 Linear Algebra II (2,2,0)3: Matrixs and linear transformations, elementary operations, elementary operations of parallel rank vectors of matrix, rank of a matrix and inverse of a matrix, concept of permutation, determinant function, determinant rank of a matrix, determinant of linear transformation, linear equation systems, vectorial multiplication in three dimensional space, properties of vectorial multiplication, combined multiplication and its applications, characteristic polynomial of a matrix, dual space, dual basis, dual of dual of a space, properties of dual space.

STAT 201 Statistical Theory I (4,0,0)4: Sigma-algebra, Borel algebra, random variable and random vector, distribution function, multivariate distributions, marginal and conditional distributions, independence of random variables, expected value, covariance, correlation coefficient, transformations of random variables, some important probability distributions, Poisson, Multinomial, Gamma, Chi-square, Weibull, student-t and F distributions, inequalities, series of random variable and convergency, the law of large numbers and central limit theorem.

STAT 202 Statistical Theory II (4,0,0)4: Sampling and concept of statistics, some sampling distributions, parameter estimation and some properties of estimators, methods of finding estimator, sufficiency and completeness, interval estimation of parameters, hypothesis testing, simple and complex hypothesis, Neyman-Pearson theorem, testing of simple hypothesis versus simple alternative, uniformly must powerful tests, testing of simple hypothesis versus complex alternative, likelihood ratio test, testing of complex hypothesis versus complex alternative, application of hypothesis testing.

STAT 203 Linear Programming (2,2,0)3: Optimization problems, mathematical modelling, duality problem, the dual simplex method, post-optimality analysis, sensitivity analysis, parametric programming.

STAT 204 Optimization (2,2,0)3: Convex, concav sets, convex and concav functions, classic optimization, discriminant method, Newton-Raphson method, Jacobian method, Lagrange method, Kuhn-Tucker conditions, modelling of nonlinear programming problems, one-variable optimization, three-point interval search method, dichotomous search method, golden section method, Fibonacci method, quadratic programming, convex programming.

STAT 205 Computer Programming III (2,2,0)3: C++ programming language, numerical calculations and some calculation errors, structural programming, program development, applications, use of MATLAB package program, MATLAB programming, web design.

STAT 206 Computer Programming IV (2,2,0)3: A last generation programming language, program development for statistical problems and inference, introduction to statistical package programs.

STAT 251 Statistical Laboratory I (0,0,2)1: Table of random numbers and random number generation in computer, experiment, sample space and random variable. Probability and distribution tables for the binomial, standard normal, chi-square and t distributions. Law of Bernoulli large numbers and central limit theorem, description of observations and analysis.

STAT 252 Statistical Laboratory II (0,0,2)1: Sampling, applications of parameter estimation and hypothesis testing, relation between data and analysis methods, statistical analysis, statistical inference and their explication studies.

MATH 257 Advanced Calculus I (4,2,0)5: Topology of , and , real and complex number systems, convergence of function series, uniformly convergence and differentiation, Fourier series and orthogonal functions, functions with limited oscillation, types of generalized integral, convergence measurement for first and second generalized integrals, Gamma and Beta functions, vector valuable functions and their analysis.

MATH 258 Advanced Calculus II (4,2,0)5: Lebesque measure, Lebesque integral, Riemann-Stieltjes integrals, inequalities of Cauchy-Schwarz, Holder, Minkowski and Jensen, Cauchy theorem and residual analysis, approximation to functions, Weirstrass and polinomial interpolation approximations, spline functions, differential equations and introduction to solution techniques.

STAT 301 Multivariate Statistical Distributions and Inference (4,0,0)4: Random vectors and theirs probability distributions, marginal and conditional distributions of random vectors, mean vectors and covariance matrices, characteristic function of the random vectors, transformations of random vectors, the multivariate normal distribution and its properties, sample mean vector and sample covariance matrix, parameter estimation, inference about a mean vector.

STAT 302 Multivariate Statistical Analysis Methods (4,0,0)4: Correlations models, Multivariate analysis of variance (MANOVA) and multivariate analysis of covariance (MANCOVA), multivariate regression, canonical correlation analysis, discriminant analysis, principal components, factor analysis, clustering, nonparametric approaches of the multivariate models.

STAT 303 Sampling (2,2,0)3: Basic concepts of sampling and an overview of sampling methods, choice of sample size, (designation of sample size), sampling designs, ratio estimator, cluster sampling, sampling methods with replacement, cost problems, design for survey researches, sampling errors and generation of optimal information.

STAT 304 Statistical Decision Theory and Methods (2,2,0)3: Bayesian inference, decision, loss and risk functions, minimax and Bayesian estimation methods, prior, posterior and conjugate prior distributions, decision problem, decision under uncertainity.

STAT305 Mathematical Fundamentals of Statistical Modeling (3,2,0)4: Modeling principles in time series, reliability analysis, risk analysis, stochastic financial analysis, stochastic processes. Difference equation, differential-difference equations, stochastic differential equations, ito formulation, functions of complex numbers (or functions in complex systems) and statistical applications, essentials of modeling on linear and nonlinear optimization, model assessments.

STAT 306 Statistical Design of Experiments (2,2,0)3: Basic concepts, experiments involving one factor, experiments involving several factors, fixed, random and mixed models, nested models, constraints on randomness in experiments involving two or more factors, split-plot designs, analysis of covariance.

STAT 307 Regression Analysis (2,2,0)3: Simple linear regression, estimation and hypothesis testing of regression parameters, multiple linear regression, polynomial regression, collinearity problem, multiple and partial correlation, residual analysis, heteroscadasticity, selection of best regression model, methods for variable selection, AIC, BIC, autocorrelation, MINMAD regression, ridge regression.

STAT 308 Time Series Analysis (2,2,0)3: Basic fundamentals of time series, stationarity, autocorrelation and partial autocorrelation functions, stationary time series models (AR, MA, ARMA, SARMA), parameter estimation, hypothesis tests, forecasting, modeling, nonstationary time series, unit root series.

STAT 309 Nonparametric Statistics (2,2,0)3: Order statistics, randomness, hypotheses of symmetry and independence, one-sample, two-sample and k-sample tests for the location and scale, goodness of fit tests, correlation and inclination tests, empirical distributions, structural models.

STAT 310 Numerical Analysis (2,2,0)3: Error analysis, solutions of linear and nonlinear system of equations, linear interpolation, finite differences, functional approximation, least square approximation, numerical integration.

STAT 312 Statistical Computing (2,2,0)3: Matrix operations in statistic with package programs, least square, numerical analysis, numerical integration, numerical solutions of differential equations, symbolic computing, methods of statistical models and analysis, their expression and computer programming.

STAT 314 Measure and Probability Theory (2,2,0)3: Measure and integration, probability measure, extension theory, determination of probability measures via distribution functions, independence, convergence in random variables series, limit theories, ergodic, martingale methods, convergence in distribution, approach theories.

STAT 316 Research Methods (2,2,0)3: Determination of the research goal and expression of problems in the statistic language, proving hypothesis, theoretical frame and determination of data collection method, preparation of research planning, collection of data and its analysis, testing of hypothesis and its interpretation, and presentation of the results.

STAT 318 Statistics for Life Sciences (2,2,0)3: Descriptive statistics, distributions, inference for multi-population samplings, linear models, categorical data, hypothesis and inference, designs of experiment and observation, bioassay, life testing and ratio testing, applications of biological and biomedical, dose and response analysis.

STAT 320 Simulation (2,2,0)3: Logic of simulation, random number generators, Monte-Carlo technique, finite variance minimization, simulations for statistical models, simulation of system, simulation analysis in decision making and interpretation.

STAT 401 Probability and Stochastic Processes (4,0,0)4: Kolmogorov’s axioms, Borel-Cantelli lemmas, zero-one law, random variables and stochastic processes, trajectories, mean value function, covariance and correlation functions, Bernoulli process, Poisson process, Markov chains, branching process, diffusion process.

STAT 402 Data Analysis (3,2,0)4: Phases of statistical data analysis, exploratory data analysis, data summary, graphical methods, steam and leaf, boxplot charts, data translation, data organization, robust lines, tables, analysis techniques, analysis of residuals, spesification of extraordinary values, analysis of truncated data, multivariate data analysis, methods of robust data analysis.
STAT 411 Statistical Software (2,2,0)3: Popular package pragrams, works on software development, software connection between statistical methods and applications, yielding software determination, software reliability, performance criterions.

STAT 412 Statistical Programming and Data Bases (2,2,0)3: Introduction to data base management system, data base usage over network and data network and statistical applications, structures of data base and statistical analysis.

STAT 413 Global Information Networks (2,2,0)3: Data systems, data transfers, network structures and network management concepts, information production and sharing in internet’ s network, internet’ s network and macro programming for multi users systems, information homepages and information dealing, databases and data mining within network structures.

STAT 414 Management Information Systems (2,2,0)3: Management systems and system analysis, information flow and reporting, structure of electronic document and archive, management in environment of network and intranet, statistical information and management information system interfaces, data information transfers and its security, design and management of wide and tight area networks information system.

STAT 415 Demography (2,2,0)3: Population dispersion and population predictions, life tables, stationary (immobile) population analysis, migrations, modelling of population events, population dynamics and demographical analysis, population characteristics and risk assessment.

STAT 416 Stochastic Modeling and Analysis (2,2,0)3: Stochastic processes, special distributions related to stochastic processes, modeling for discrete and continuous processes, parametric and nonparametric estimation techniques, hypothesis testing and inference, data analysis and techniques with time and spatial dynamics.

STAT 417 Linear Models (2,2,0)3: Generalized inverse of a matrix, distributions of quadratic forms of normal random vectors, general linear models, structures of generalized model, all kinds of linear models in components of discrete and continuous random variables, inference of linear models.

STAT 418 Econometrics (2,2,0)3: Type of data and source of data, properties of LS estimators and Gauss Markov Theorem, normality assumption, classical linear regression model, mathematical structures in economic theory, linear structures, semi logarithmic structures, parabolic structure and concept of elesticity, restricted LS, generalized LS, multicollinearity, heteroskedasticity, autocorrelation, simultaneous equations models, econometric time series models.

STAT 419 Multivariate Time Series (2,2,0)3: Vector time series, stationary, autocovariance and autocorrelation matrixs, non-stationary multivariate time series and concept of cointegration, Methods of Engle- Granger and Johansen.

STAT 420 Discrete Multivariate Data Analysis (2,2,0)3: Multi directional crosstables and their analysis, loglinear models, logit and probit models, logistic regression, popular methods and applications.

STAT 421 Spatial Statistics (2,2,0)3: Introduction to spatial analysis, descriptive techniques and moments and functions of measuring spatial relations, Lattice and Grid Models, Pattern analysis, variodogram models, random sets.

STAT 422 Pattern Recognition and Analysis (2,2,0)3: Pattern structures, pattern textures and designs, attended and unattended pattern recognition, descriptive techniques, modeling and solutions, parameter estimation and hypothesis testing in pattern recognition and analysis.

STAT 423 Risk Management (2,2,0)3: Definition of risk, risk management areas, hazards-perils-losses systematic, claim distributions, assessment of risk and risk analysis techniques, methods of making decisions about risk, planning and application of precautions against risk, risk management systems.

STAT 424 Actuarial Risk Analysis(2,2,0)3: Actuarial risk, claim distributions, risk processes, ruin probability and solvency analysis, actuarial risk in short term and long term, life insurance, pension funds and tecnical analysis methods for other insurance fields.

STAT 425 Reliability Analysis (2,2,0)3: Basic concepts of reliability theory and their equivalences in sample, Poisson, Gamma, exponential, Weibull and log-normal models, point and interval estimations for corruption time (failure time) statistical inference for rest of life.

STAT 426 Financial Risk Analysis (2,2,0)3: Financial markets, options and derivatives, financial risk measurement, risk capital, credit risk, investment risk, financial risk management and statistical techniques, measurement of risk in finance markets and risk minimization, stochastic analysis and financial applications.

STAT 427 Statistical Quality Control (2,2,0)3: Basic concepts, lot control, production control, process control and statistical methods, taguchi methods, six-sigma, quality standards, total quality control, multi dimensional and multivariate statistical quality assesments.

STAT 428 Inventory Theory (2,2,0)3: Introduction to principal inventory models, supply model, production model, production model in unholding cases, supply model in holding cases, changes in time period, Q model in case of cost reducing, dinamic inventory models with N periods, EOQ model in the event of compound by custom-made, probabilistic inventory models.

STAT 429 Game Theory (2, 2, 0) 3: Two –person Zero-Sum and constant sum games, saddle points, mixed strategies, zero-sum games and linear programming, n-person games, two-person general sum games, decision with perfect and imperfect information prior information and optimal solution of games, statistical decision problems and other applications.

STAT 430 Queueing Theory (2,2,0)3: General queue system, basic concepts, Kendal Lee- Taha notation, arrival and service processes modeling, birth and death processes, unique splined queue models, multi splined queue models, analysis of queue problems with finite arrival source, queue models with Poisson arrival and Erlang service process, serial systemic queues, queue decision models.

STAT 431 Statistical Methods for Clinical Trials (2,2,0)3: Data compositions, research design and protocol development, individual and group therapy trials, comparisons inter-therapies and connecting estimation, simple and mixed implantations, estimation and testings with design models, lengthways researchs, meta analysis, Bayesian and sequential analysis, applications.

STAT 432 Statistical Genetics (2,2,0)3: Principles of population genetics, gene counting and EM algorithm, scoring, estimation and testing about genotype, relationship coefficient and coefficient of belonging, possibilities of Mendel, genotype and haplotype analysis, poligenic models, molecular filogeny, hybrid mapping, recombination models, sequence analysis, stochastic models and inferences.

STAT 433 Operations Research (2,2,0)3: Transportation, assignment and transhipment problems, network models, integer programming, dynamic programming, application of optimization theory on systems and processes.

STAT 434 Multicriteria Decision Making (2,2,0)3: Problem modelling, determination of criteria and objective for complex decisions , multiobjective decision making methods used as alternative finite number of closed constraints, collective criteria method , methods demanding the prior knowledge about objectives at beginning of the problem, interactive multiobjective decision making methods , goal programming , multiobjective simplex method.

STAT 435 Decision Support Systems (2,2,0)3: Data-Information-Decision theories and characteristics, decision structures, information systems, concept of decision support system, components of decision support system, management of data and model, decision support system in decision making and relation of management informatics system, operational research in decision support system, analytic, hierarchy methods, introduction to expert systems, data store and usage of data mining for decision processes.

STAT 436 Production Planning and Industrial Statistics (2,2,0)3: Statistical estimation and forecasting techniques for production planning, stochastic models and production planning, production processes, control models, inventory control, production and quality control, statistical techniques for macro and micro industrial processes in design and application, economic indicator and sectoral interpretation.

STAT 451 Special Topic (0,0,2)1: Interpretation and inference of data, analysis and evaluate for statistical procedure and models, their applications, analysis and report.

STAT 452 Special Topic (0,0,2)1: Interpretation and inference of data, analysis and evaluate for statistical procedure and models, their applications, analysis and report, knowledge production and examine of useful applications.