MME901M Statistical Methods for Economists

School of Business Administration in Karvina
Winter 2007
Extent and Intensity
1/2/0. 5 credit(s). Type of Completion: z (credit).
Teacher(s)
Ing. Elena Mielcová, Ph.D. (lecturer)
Ing. Elena Mielcová, Ph.D. (seminar tutor)
Ing. Filip Tošenovský, Ph.D. (seminar tutor)
Guaranteed by
Ing. Elena Mielcová, Ph.D.
Department of Informatics and Mathematics – School of Business Administration in Karvina
Course Enrolment Limitations
The course is also offered to the students of the fields other than those the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives (in Czech)
At the end of this course, students should get a deeper knowledge of statistical methods suitable for processing multidimensional data, know the theoretical methods, and be able to apply them by using statistical programs on PC. The course will introduce the principles of special economical-statistical methods for quality control and quality management. Knowledge of these methods will allow students to control and operate effectively a quality of production at all stages, which includes a pre-production, production and post-production phase. They will also manage methods that are required by international standards, such as American OS 9000 or German VDA 6.1. These norms are obligatory for many industries, for example for all suppliers in the automotive industry.
Syllabus (in Czech)
  • Structure of the Course:
    1. Panel Data, Data Matrices
    2. Multinomial Regression and Correlation Analysis
    3. Design of Experiments
    4. Multidimensional Analysis of Variance (ANOVA)
    5. Taguchi on-line Methods (production stages)
    6. Regulation diagrams
    7. Evaluation of the Capability of Technological Process
    Content of the course:
    1. Panel data, data matrices.
    Random variable, data types, data matrices, objects and variables, time part in random variable.
    2. Multinomial Regression and Correlation Analysis.
    Dependency of observations, basic definitions of regression, correlation, regression model and its classifications, simple linear regression model, multinomial linear regression model, parameter estimations, interval estimations, tests of statistical significance of the parameters, heteroskedasticity, autocorrelation, multicollinearity, non-linear models, dependency of quality values, contingency tables.
    3. Design of Experiments
    Economics of statistical experiments, one-factor plan design, full-factor plan, half-plans, application of the experimental design, design of robust technologies, methods of experiments evaluation for various number of block variables.
    4. Multidimensional Analysis of Variance
    Aim of the analysis of variance, division total variability to predefined parts, one-dimensional problems with one factor, multidimensional problems with one factor, and problems with more factors.
    5. Taguchi on-line methods (stage: production)
    Definition and properties of the Taguchi loss function L(Y), application of the loss function, determination of the total quality control cost and methods for its minimization, optimization of the control regime.
    6. Regulation diagrams (stage: production)
    Normal and non-normal distribution function of quality variable, piece production.
    7. Evaluation of the Capability of Technological Process (stage: after production)
    One-dimensional and multidimensional quality indices (for normal and random distribution of data), methods of indices` tests, estimation of defective products, computation of production process robustness

    Presentation media and PC are used in the framework of education. Seminars are taught in computer classrooms. Educational materials in electronic form are available on faculty computer network.
Language of instruction
English
Further comments (probably available only in Czech)
The course can also be completed outside the examination period.
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