| Course Unit Code | 470-4404/01 |
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| Number of ECTS Credits Allocated | 4 ECTS credits |
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| Type of Course Unit * | Compulsory |
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| Level of Course Unit * | Second Cycle |
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| Year of Study * | First Year |
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| Semester when the Course Unit is delivered | Summer Semester |
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| Mode of Delivery | Face-to-face |
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| Language of Instruction | Czech |
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| Prerequisites and Co-Requisites | Course succeeds to compulsory courses of previous semester |
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| Name of Lecturer(s) | Personal ID | Name |
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| LIT40 | Ing. Martina Litschmannová, Ph.D. |
| KRA0220 | Ing. Jan Kracík, Ph.D. |
| Summary |
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| This is an introductory course in statistics. The course will emphasize methods of applied statistics and data analysis. Theoretical considerations will be included to the extent that knowledge of theory is necessary for a sound understanding of methods and contributes to the development of data analysis skills and the ability to interpret results of statistical analysis. The objective of the course is to develop sufficient knowledge of statistical tools and procedures, understanding of the underlying theory on which the procedures are based, and facility in the application of statistical tools to enable the student to incorporate sound statistical methodology into other areas of his or her own work. |
| Learning Outcomes of the Course Unit |
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| This is an introductory course in statistics. The course will emphasize methods of applied statistics and data analysis. |
| Course Contents |
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Lectures:
Exploratory data analysis, types of variables,
Exploratory analysis of single discrete and continuous variables, summarization of distributions.
Probability theory.
Random variable and probability distribution, expected value operator and moments of probability distribution,
joint and conditional distributions.
Probability models for discrete and continuous random variables.
Sampling distributions of the mean, distribution of sample proportion
Central Limit Theorem.
Point and interval estimation.
Hypothesis testing, pure significance tests, p-values Two sample tests, paired difference tests.
One factor analysis of variance, ANOVA table, multiple comparisons, post hoc analysis.
Simple linear regression model, least squares estimation of parameters and properties of the estimates.
Multiple regression models. |
| Recommended or Required Reading |
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| Required Reading: |
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Briš R., Probability and Statistics for Engineers, Elektronické skriptum VŠB TU Ostrava,2011, projekt Rozvoj jazykových kompetencí pracovníků VŠB-TU Ostrava: InterDV, registrační číslo: CZ.1.07/2.2.00/15.0132
Dummer R.M.; Introduction to Statistical Science, skriptum VŠB-TUO FEI, 1998, ISBN 80-7078-497-0 |
| Briš R., Litschmannová M.,BIOSTATISTIKA pro kombinované a distanční studium, Elektronické skriptum VŠB TU Ostrava,2008 |
| Recommended Reading: |
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| Dummer R.M.; Introduction to Statistical Science, skriptum VŠB-TUO FEI, 1998, ISBN 80-7078-497-0 |
Hebák P. a kol., Vícerozměrné statistické metody, Informatotium 2004
Likeš J., Machek J., Počet pravděpodobnosti, SNTL Praha 1981
Likeš J., Machek J., Matematická statistika, SNTL Praha 1983 |
| Planned learning activities and teaching methods |
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| Lectures, Tutorials, Project work |
| Assesment methods and criteria |
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| Task Title | Task Type | Maximum Number of Points
(Act. for Subtasks) | Minimum Number of Points for Task Passing |
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| Exercises evaluation and Examination | Credit and Examination | 100 (100) | 51 |
| Exercises evaluation | Credit | 40 (40) | 20 |
| Průběžné testy | Written test | 20 | 6 |
| SP | Semestral project | 20 | 10 |
| Examination | Examination | 60 (60) | 27 |
| Praktická část | Written examination | 50 | 25 |
| Teoretická část | Written examination | 10 | 2 |