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Lecturer(s)
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Homolka Lubor, Ing. Ph.D.
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Course content
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Repetition of basic concepts, software possibilities of statistical data processing Application of contingency and association tables in marketing and sociological research Analysis of variance ? applications in statistical quality management Nonparametric tests - situations when to use parametric and nonparametric tests Application of regression and correlation analysis in various areas of industry Multiple regression and correlation ? emphasis on interpretation of model parameters Parametric and nonparametric measures of dependence tightness or when to use parametric and nonparametric correlation coefficients in practice Introduction to time series, additive and multiplicative econometric model Analytical and mechanical balancing of time series with practical examples on financial data Introduction to machine learning - applications of machine learning in various industrial areas (machine learning with and without a teacher) Introduction to machine learning - applications of machine learning in various industrial areas (difference between prediction and classification)
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Learning activities and teaching methods
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unspecified
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| learning outcomes |
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| Knowledge |
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| Defines the difference between descriptive and inferential statistics |
| Defines the difference between descriptive and inferential statistics |
| Defines what a dependence between variables of a statistical population is |
| Defines what a dependence between variables of a statistical population is |
| Explains the difference between different tests of dependence |
| Explains the difference between different tests of dependence |
| Describes the principle of time series |
| Describes the principle of time series |
| Explains the difference between parametric and non-parametric tests |
| Explains the difference between parametric and non-parametric tests |
| Skills |
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| Calculate tests related to a contingency table |
| Calculate tests related to a contingency table |
| Calculate the ANOVA test |
| Calculate the ANOVA test |
| Calculate regression and correlation analysis |
| Calculate regression and correlation analysis |
| Calculate the complete procedure for testing a statistical hypothesis |
| Calculate the complete procedure for testing a statistical hypothesis |
| Evaluates the result of a given statistical test |
| Evaluates the result of a given statistical test |
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Recommended literature
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FELLER. An Introduction to Probability Theory and Its Applications, Volume II.. New York: Wiley, 1971.
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FREUND, J. E., WALPOLE, R. E. Mathematical Statistics.. Englewood Cliffs: Prantice-Hall, 1987. ISBN 0135621178.
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JAMES, G., WITTEN, D., HASTIE, T., TIBSHIRANI, R. An introduction to statistical learning: with applications in R. New York: Springer, 2013. ISBN 978-1-4614-7137-0.
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KUHN, M., JOHNSON, K. Applied predictive modeling. New York: Springer, 2013. ISBN 978-1-4614-6848-6.
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MONTGOMERY, D. C. Introduction to Statistical Quality Control. vyd. 6.. John Wiley & Sons, Inc,, 2009. ISBN 978-0470169926.
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PECK, R., OLSEN, CH., DEVORE, J., L. Introduction to Statistics and Data Analysis, Enhanced Review Edition (4th Edition). Duxbury Press, 2011. ISBN 0840054904.
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PESTMAN, W. R. Mathematical Statistics: An Introduction. New York: Walter de Gruyter, 1998.
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ROSS, S. M. Introductory Statistics. 3rd ed.. Academic Press,, 2010. ISBN 0123743885.
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ROSS, S. M. Introductory Statistics. 3rd ed.. Academic Press, 2010. ISBN 0123743885.
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