Gurantor department | Department of Quality Management | Credits | 4 |

Subject guarantor | prof. RNDr. Josef Tošenovský, CSc. | Subject version guarantor | prof. RNDr. Josef Tošenovský, CSc. |

Study level | undergraduate or graduate | Requirement | Compulsory |

Year | 1 | Semester | winter |

Study language | English | ||

Year of introduction | 2019/2020 | Year of cancellation | |

Intended for the faculties | FMT | Intended for study types | Follow-up Master |

Instruction secured by | |||
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Login | Name | Tuitor | Teacher giving lectures |

TOS012 | Ing. Filip Tošenovský, Ph.D. | ||

TOS40 | prof. RNDr. Josef Tošenovský, CSc. |

Extent of instruction for forms of study | ||
---|---|---|

Form of study | Way of compl. | Extent |

Full-time | Credit and Examination | 2+2 |

Knowledge of basic statistical methods
Analysis of real data
Ability to process correctly experimental data
Managing work with Excel

Lectures

Tutorials

The primary aim of the subject is an exposition of the theory of estimation of population parameters, hypothesis testing, modelling of technological processes with regression models and their assessment by correlation analysis. Multivariate regression is taught under the required theoretical conditions. Correlation analysis shows ways of measuring dependence for various types of variables.

JAMES, G., D. WITTEN, T. HASTIE a R. TIBSHIRANI. An Introduction to Statistical Learning. NY: Springer, 2013. ISBN 978-1-4614-7138-7.
DRAPER, N. R. and H. SMITH. Applied Regression Analysis. NY: Wiley, 1998. ISBN 978-0471170822.
RYAN, T. P. Modern Regression Methods. NY: Wiley, 2008. ISBN 978-0470550441.
ASHENFELTER, O. B.,P. B. LEVINE and D. J. ZIMMERMAN. Statistics and Econometrics: Methods and Applications. NY: Wiley, 2006. ISBN-13: 978-0470009451.

MONTGOMERY, D. C. Applied Statistics and Probability for Engineers. NY: Wiley, 2010. ISBN-13 978-1-1185-3971-2.
SHESKIN, D. J. Handbook of Parametric and Nonparametric Statistical Procedures. NY: Chapman and Hall, 2003. ISBN 1-58488-440-1.

Written form - test.
Essay.

80% attendance in seminars

Subject has no prerequisities.

Subject has no co-requisities.

1. Introduction to statistics – explanation of its use in metallurgy. Graphical representation of data samples, assessment of data type. General principles of testing.
2. Confirmation of data sample homogeneity using graphs. Outliers – their depiction, detection (box plot) and solution.
3. Confirmation of data independence using graphs. Effect of data dependence on quality of data sample processing.
4. Confirmation of normality: normal distribution, Gauss curve and its parameters, empirical histogram. Reasons why normality is required, and procedures to be followed if the normality condition is not met.
5. Descriptive characteristics of location, variability, skewness and kurtosis. The notion of robustness of numerical characteristics.
6. Student’s distribution, Fisher’s distribution, Pearson’s distribution and their graphs. Examples of using the distributions. Use of tables of quantiles and critical values.
7. Point estimation and confidence intervals. „Confidence level“ and „nivel of test“.
8. Analysis of two data samples. Testing the difference of expected values and variances. Two-sample t-test, F-test.
9. Evaluating a measure of dependence (correlation) of two variables: Pearson’s correlation coefficient, Spearman’s rank correlation coefficient.
10. Regression analysis – simple (paired) linear regression. Estimation of regression coefficients by least squares. Assessment of significance and quality of the regression function. Simple nonlinear regression models (power, exponential, logarithmic, quadratic and polynomial models).
11. Regression analysis – multivariate linear regression. Assessment of significance of the model and its regression coefficients. Use of multivariate regression.

Task name | Type of task | Max. number of points
(act. for subtasks) | Min. number of points |
---|---|---|---|

Credit and Examination | Credit and Examination | 100 (100) | 51 |

Credit | Credit | 40 | 20 |

Examination | Examination | 60 | 31 |

Show history

Academic year | Programme | Field of study | Spec. | Zaměření | Form | Study language | Tut. centre | Year | W | S | Type of duty | |
---|---|---|---|---|---|---|---|---|---|---|---|---|

2021/2022 | (N0413A270003) Quality Management and Control of Industrial Systems | MPZ | P | English | Ostrava | 1 | Compulsory | study plan | ||||

2020/2021 | (N0413A270003) Quality Management and Control of Industrial Systems | MPZ | P | English | Ostrava | 1 | Compulsory | study plan | ||||

2019/2020 | (N0413A270003) Quality Management and Control of Industrial Systems | MPZ | P | English | Ostrava | 1 | Compulsory | study plan |

Block name | Academic year | Form of study | Study language | Year | W | S | Type of block | Block owner |
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