Administracja Centralna Uczelni - Wymiana międzynarodowa (S1)
Sylabus przedmiotu Statistics:
Informacje podstawowe
| Kierunek studiów | Wymiana międzynarodowa | ||
|---|---|---|---|
| Forma studiów | studia stacjonarne | Poziom | pierwszego stopnia |
| Tytuł zawodowy absolwenta | |||
| Obszary studiów | — | ||
| Profil | |||
| Moduł | — | ||
| Przedmiot | Statistics | ||
| Specjalność | przedmiot wspólny | ||
| Jednostka prowadząca | Katedra Technologii Wytwarzania | ||
| Nauczyciel odpowiedzialny | Marcin Chodźko <Marcin.Chodzko@zut.edu.pl> | ||
| Inni nauczyciele | |||
| ECTS (planowane) | 4,0 | ECTS (formy) | 4,0 |
| Forma zaliczenia | zaliczenie | Język | angielski |
| Blok obieralny | — | Grupa obieralna | — |
Formy dydaktyczne
Wymagania wstępne
| KOD | Wymaganie wstępne |
|---|---|
| W-1 | Mathematics, basics of probability theory. |
Cele przedmiotu
| KOD | Cel modułu/przedmiotu |
|---|---|
| C-1 | The course introduces the theoretical basis of statistical analysis. |
| C-2 | The course will introduce the most common methods and statistical models used in engineering. |
| C-3 | The course will familiarize you with the use of popular tools used in computer-aided statistical analyzes. |
Treści programowe z podziałem na formy zajęć
| KOD | Treść programowa | Godziny |
|---|---|---|
| laboratoria | ||
| T-L-1 | Solving theoretical tasks in the field of: Desciptive statistics. Inferential Statistics. Distributions. | 4 |
| T-L-2 | Solving theoretical tasks in the field of: Bivariate Data. Pearson Correlation. | 2 |
| T-L-3 | Solving theoretical tasks in the field of: Binomial distribution. Poisson distribution. Multinomial and hypergeometric distribution. | 2 |
| T-L-4 | Solving theoretical tasks in the field of: Normal distribution. Standard normal distribution. Normal aproximation to the Binomial. | 2 |
| T-L-5 | Solving theoretical tasks in the field of: Estimation. Degrees of freedom. Characteristics of estimators. Confidence intervals. | 4 |
| T-L-6 | Solving theoretical tasks in the field of: Hypothesis testing. Type I and II errors. Steps in hypothesis testing. | 2 |
| T-L-7 | Using computer aided tools for solving problems in field of: Hypothesis testing. Type I and II errors. Steps in hypothesis testing. | 2 |
| T-L-8 | Using computer aided tools for solving problems in field of: Testing means.Testing between two means (independent and correlated) | 4 |
| T-L-9 | Using computer aided tools for solving problems in field of: Regression. Introduction to linear regression. R. Introduction to multiple regression. | 4 |
| T-L-10 | Using computer aided tools for solving problems in field of: Analysis of Variance - basics ANOVA | 4 |
| 30 | ||
| wykłady | ||
| T-W-1 | Introduction. Variables. Desciptive statistics. Inferential Statistics. Distributions. | 2 |
| T-W-2 | Graphing distributions. Histograms. Plots, Charts and Graphs. | 2 |
| T-W-3 | Central Tendency. Shapes of Distributions. Measures of Variability. | 2 |
| T-W-4 | Bivariate Data. Pearson Correlation. | 2 |
| T-W-5 | Probability. Binomial distribution. Poisson distribution. Multinomial and hypergeometric distribution. | 2 |
| T-W-6 | Normal distribution. Standard normal distribution. Normal aproximation to the Binomial. | 2 |
| T-W-7 | Estimation. Degrees of freedom. Characteristics of estimators. Confidence intervals. | 2 |
| T-W-8 | Hypothesis testing. Type I and II errors. Steps in hypothesis testing. | 2 |
| T-W-9 | Testing means.Testing between two means (independent and correlated) | 4 |
| T-W-10 | Regression. Introduction to linear regression. R. Introduction to multiple regression. | 6 |
| T-W-11 | Analysis of Variance - basics ANOVA | 4 |
| 30 | ||
Obciążenie pracą studenta - formy aktywności
| KOD | Forma aktywności | Godziny |
|---|---|---|
| laboratoria | ||
| A-L-1 | Participation in classes | 30 |
| A-L-2 | Independent work on tasks | 20 |
| 50 | ||
| wykłady | ||
| A-W-1 | Participation in classes | 30 |
| A-W-2 | Self-reliant exercises. | 20 |
| 50 | ||
Metody nauczania / narzędzia dydaktyczne
| KOD | Metoda nauczania / narzędzie dydaktyczne |
|---|---|
| M-1 | Lecture information using oral presentation and examples. |
| M-2 | Group and individual work on problems given by a teacher. |
| M-3 | Practicing, statistics problems solving and results discussion. |
Sposoby oceny
| KOD | Sposób oceny |
|---|---|
| S-1 | Ocena formująca: Periodical check-ups of the statistics knowledge by the students in a form of exercising tasks. |
| S-2 | Ocena formująca: Transitional evaluation of the state of progress of overall knowledge. |
| S-3 | Ocena podsumowująca: The completion of the lecture is based on the attendance list and the verification test. |
Zamierzone efekty uczenia się - wiedza
| Zamierzone efekty uczenia się | Odniesienie do efektów kształcenia dla kierunku studiów | Odniesienie do efektów zdefiniowanych dla obszaru kształcenia | Cel przedmiotu | Treści programowe | Metody nauczania | Sposób oceny |
|---|---|---|---|---|---|---|
| WM-WIMiM_1-_WM50_W01 The student can characterize random variables. Explain the methods of estimating the parameters of random variables. Explain the concept of statistical hypothesis and the principles of its verification. Describe ways to estimate the interdependencies between random variables. | — | — | C-1, C-2, C-3 | T-W-1, T-W-2, T-W-3, T-W-4, T-W-5, T-W-6, T-W-7, T-W-8, T-W-9, T-W-10, T-W-11 | M-1, M-3 | S-3, S-1, S-2 |
Zamierzone efekty uczenia się - umiejętności
| Zamierzone efekty uczenia się | Odniesienie do efektów kształcenia dla kierunku studiów | Odniesienie do efektów zdefiniowanych dla obszaru kształcenia | Cel przedmiotu | Treści programowe | Metody nauczania | Sposób oceny |
|---|---|---|---|---|---|---|
| WM-WIMiM_1-_WM50_U01 The student is able to develop and interpret the results of experimental research. Choose appropriate statistical tests to verify basic statistical hypotheses and verify them. Calculate the correlation coefficient and estimate the regression relationship. | — | — | C-3 | T-L-1, T-L-2, T-L-3, T-L-4, T-L-5, T-L-6, T-L-7, T-L-8, T-L-9, T-L-10 | M-2 | S-2 |
Zamierzone efekty uczenia się - inne kompetencje społeczne i personalne
| Zamierzone efekty uczenia się | Odniesienie do efektów kształcenia dla kierunku studiów | Odniesienie do efektów zdefiniowanych dla obszaru kształcenia | Cel przedmiotu | Treści programowe | Metody nauczania | Sposób oceny |
|---|---|---|---|---|---|---|
| WM-WIMiM_1-_WM50_K01 Student is aware of the need for continuous training in the development and analysis of observed experimental data. | — | — | C-3 | T-L-1, T-L-2, T-L-3, T-L-4, T-L-5, T-L-6, T-L-7, T-L-8, T-L-9, T-L-10 | M-2 | S-2 |
Kryterium oceny - wiedza
| Efekt uczenia się | Ocena | Kryterium oceny |
|---|---|---|
| WM-WIMiM_1-_WM50_W01 The student can characterize random variables. Explain the methods of estimating the parameters of random variables. Explain the concept of statistical hypothesis and the principles of its verification. Describe ways to estimate the interdependencies between random variables. | 2,0 | |
| 3,0 | Fluent solving of given problem within the subject | |
| 3,5 | ||
| 4,0 | ||
| 4,5 | ||
| 5,0 |
Kryterium oceny - umiejętności
| Efekt uczenia się | Ocena | Kryterium oceny |
|---|---|---|
| WM-WIMiM_1-_WM50_U01 The student is able to develop and interpret the results of experimental research. Choose appropriate statistical tests to verify basic statistical hypotheses and verify them. Calculate the correlation coefficient and estimate the regression relationship. | 2,0 | |
| 3,0 | Fluent solving of given problem within the subject | |
| 3,5 | ||
| 4,0 | ||
| 4,5 | ||
| 5,0 |
Kryterium oceny - inne kompetencje społeczne i personalne
| Efekt uczenia się | Ocena | Kryterium oceny |
|---|---|---|
| WM-WIMiM_1-_WM50_K01 Student is aware of the need for continuous training in the development and analysis of observed experimental data. | 2,0 | |
| 3,0 | Fluent solving of given problem within the subject | |
| 3,5 | ||
| 4,0 | ||
| 4,5 | ||
| 5,0 |
Literatura podstawowa
- Douglas C. Montgomery, Applied Statistics and Probability for Engineers, A. John Wiley & Sons, Inc., 2003
- T.T. Soong, Fundamentals of Probability and Statistics for Engineers, John Wiley & Sons, Inc., 2004
Literatura dodatkowa
- Joaquim P. Marques de Sá, Applied Statistics Using SPSS, STATISTICA, MATLAB, Springer, 2007