MME902M Time Series Analysis

School of Business Administration in Karvina
Winter 2007
Extent and Intensity
1/2/0. 5 credit(s). Type of Completion: z (credit).
Teacher(s)
Mgr. Radmila Krkošková, Ph.D. (lecturer)
Mgr. Radmila Krkošková, Ph.D. (seminar tutor)
Ing. Filip Tošenovský, Ph.D. (seminar tutor)
Guaranteed by
Mgr. Radmila Krkošková, 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
there are 12 fields of study the course is directly associated with, display
Course objectives (in Czech)
The course objective is to introduce the students with statistical methods used in economic time series analysis, e.g. classical decomposition methods, Box-Jenkinson methodology, spectral methods. Solving of practical problems by using these methods on personal computer is emphasised.
Syllabus (in Czech)
  • Structure of the Course:
    1. Importance, basic approaches and specific problems in time series analysis
    2. Decomposition of time series
    3. Box-Jenkinson methodology and spectral analysis
    4. Utilization of statistical software on PC
    Content of the course:
    1. Importance, basic approaches and specific problems in time series analysis.
    Dynamics of economic behaviour, interval and point indicators, chronologic average, additive and multiplicative models, one-dimensional and multi-dimensional models, time component, basic characteristics.

    2. Decomposition of time series
    Trend, seasonal and erratic component, choosing the adequate model, seasonal models, adaptive models, exponential smoothing.
    3. Box-Jenkinson methodology and spectral analysis
    Autoregressive models AR, moving average models MA, models ARMA and ARIMA, extrapolation and forecasting of time series, measuring forecasting accuracy, spectral analysis. Stationary stochastic processes, autocovariance matrix, autocorrelation function, advantages and disadvantages of autocorrelation function for time series analysis.
    4. Utilization of statistical software on PC
    Microsoft Excel, SPSS and their utilization for solving practical problems on PC.

    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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