Zachodniopomorski Uniwersytet Technologiczny w Szczecinie

Administracja Centralna Uczelni - Wymiana międzynarodowa (S1)

Sylabus przedmiotu Data Analysis, Interpretation and Presentation:

Informacje podstawowe

Kierunek studiów Wymiana międzynarodowa
Forma studiów studia stacjonarne Poziom pierwszego stopnia
Tytuł zawodowy absolwenta
Obszary studiów
Profil
Moduł
Przedmiot Data Analysis, Interpretation and Presentation
Specjalność przedmiot wspólny
Jednostka prowadząca Katedra Mechaniki Konstrukcji
Nauczyciel odpowiedzialny Zbigniew Sekulski <Zbigniew.Sekulski@zut.edu.pl>
Inni nauczyciele
ECTS (planowane) 6,0 ECTS (formy) 6,0
Forma zaliczenia zaliczenie Język angielski
Blok obieralny Grupa obieralna

Formy dydaktyczne

Forma dydaktycznaKODSemestrGodzinyECTSWagaZaliczenie
wykładyW1 30 2,50,40zaliczenie
ćwiczenia audytoryjneA1 30 3,50,60zaliczenie

Wymagania wstępne

KODWymaganie wstępne
W-1Fundamentals of probability theory.

Cele przedmiotu

KODCel modułu/przedmiotu
C-1To give relevant skills to presentation and analysis of collected data for research, commercial, industrial and marketing activities as well as professional practices.

Treści programowe z podziałem na formy zajęć

KODTreść programowaGodziny
ćwiczenia audytoryjne
T-A-1The solution of exercises related to issues discussed during lectures.28
T-A-2Skills evaluation.2
30
wykłady
T-W-1Elements of statistics: cases, variables, types of variables; matrix and frequency table; graphs and shapes of distributions; mode, median and mean; range, interquartile range and box plot, variance and standard deviation; Z-scores; contingency table, scatterplot, Pearson’s r; basics of regression; elementary probability; random variables and probability distributions (Normal Distribution, Binomial Distribution & Poisson Distribution).4
T-W-2Inferential statistics: observational studies and experiments; sample and population, population distribution, sample distribution and sampling distribution; Central Limit Theorem; point estimates, confidence intervals, introduction to hypothesis testing.4
T-W-3Measures of distribution shape: skewness and kurtosis. Skewness and kurtosis application to normality test.2
T-W-4How to use statistics to identify outliers in data (what are outliers and how to deal with them?): what are the outliers, types of outliers, most common causes of outliers on a data set (data entry errors(human errors), measurement errors (instrument errors), experimental errors (data extraction or experiment planning/executing errors), intentional (dummy outliers made to test detection methods), data processing errors (data manipulation or data set unintended mutations), sampling errors (extracting or mixing data from wrong or various sources), natural (not an error, novelties in data)).4
T-W-5Some of the most popular methods for outlier detection (Z-score or extreme value analysis, probabilistic and statistical modelling, linear regression models, proximity based models, information theory models, high dimensional outlier detection methods).4
T-W-6Evaluation of the uncertainty of measurement: measurant, uncertainty of measurement and measurement error, systematic and random errors (uncertainties), uncertainty of measurement and GUM terminology (Evaluation of Measurement Data - Guide to the Expression of uncertainty in measurement; usually referred to as the GUM), type a and type b uncertainties, degrees of freedom and uncertainty in the uncertainty, functional relationships, input and output quantities, propagation of uncertainty, uncertainty components when the inputs are uncorrelated, uncertainty components when the inputs are correlated, summary of procedure for determining the propagation of uncertainty, precision profile and uncertainty of measurement, rules for calculating uncertainty through functional relationships.4
T-W-7How people interpret data visualization and presentation. How to interpret uncertainty in common forms of data visualizations.2
T-W-8Statistical significance problem.2
T-W-9Final comment.2
T-W-10Evaluation of knowledge.2
30

Obciążenie pracą studenta - formy aktywności

KODForma aktywnościGodziny
ćwiczenia audytoryjne
A-A-1Class participation and active engagement for developing and refining students ability to critically and productively engage with the subjects being studied.30
A-A-2Preparation of homeworks and exercises.52
A-A-3Preparation to skills evaluation.5
87
wykłady
A-W-1Participation in classes.30
A-W-2Self study.22
A-W-3Preparation to knowledge evaluation.10
62

Metody nauczania / narzędzia dydaktyczne

KODMetoda nauczania / narzędzie dydaktyczne
M-1Lectures
M-2Exercises

Sposoby oceny

KODSposób oceny
S-1Ocena formująca: Student attendance and participation in class sessions play a vital role in successful course completion.
S-2Ocena podsumowująca: Students will be expected to complete written tests, projects and homework assignments as specified by the teacher.

Zamierzone efekty uczenia się - wiedza

Zamierzone efekty uczenia sięOdniesienie do efektów kształcenia dla kierunku studiówOdniesienie do efektów zdefiniowanych dla obszaru kształceniaCel przedmiotuTreści programoweMetody nauczaniaSposób oceny
WM-WTMiT_1-_WM-WTMiT_W01
To give relevant skills to presentation and analysis of collected data for research, commercial, industrial and marketing activities as well as professional practices. It helps in obtaining information from it as the raw data is non-comprehensive in nature.
C-1T-W-1, T-W-5, T-W-9, T-W-2, T-W-4, T-W-3, T-W-7, T-W-6M-1S-2, S-1

Zamierzone efekty uczenia się - umiejętności

Zamierzone efekty uczenia sięOdniesienie do efektów kształcenia dla kierunku studiówOdniesienie do efektów zdefiniowanych dla obszaru kształceniaCel przedmiotuTreści programoweMetody nauczaniaSposób oceny
WM-WTMiT_1-_WM-WTMiT_U01
The ability to use the acquired knowledge to solve practical problems.
C-1T-A-1M-2S-2, S-1

Zamierzone efekty uczenia się - inne kompetencje społeczne i personalne

Zamierzone efekty uczenia sięOdniesienie do efektów kształcenia dla kierunku studiówOdniesienie do efektów zdefiniowanych dla obszaru kształceniaCel przedmiotuTreści programoweMetody nauczaniaSposób oceny
WM-WTMiT_1-_WM-WTMiT_K01
Improvement of social and personal competencies including self-awareness, self-management, social awareness, relationship skills, responsible decision-making and others. Encouraging dialogue and mutual respect between peoples of different nations, cultures and faiths.
C-1T-A-1M-2, M-1S-2, S-1

Kryterium oceny - wiedza

Efekt uczenia sięOcenaKryterium oceny
WM-WTMiT_1-_WM-WTMiT_W01
To give relevant skills to presentation and analysis of collected data for research, commercial, industrial and marketing activities as well as professional practices. It helps in obtaining information from it as the raw data is non-comprehensive in nature.
2,0Failing, Students performing at this level demonstrate no evidence of the knowledge, skills, and practices embodied by the course assessed at their grade level. The range for the grade of 2.0 is from 0% to 50% of the total possible score (100%).
3,0Acceptable, Students performing at this level demonstrate a minimal command of the knowledge and/or skills embodied by the course assessed at their grade level. The range for the grade of 3.0 is from 51% to 60% of the total possible score (100%).
3,5Below Average, Students performing at this level demonstrate a beginning command of the knowledge and/or skills embodied by the course assessed at their grade level. The range for the grade of 3.5 is from 61% to 70% of the total possible score (100%).
4,0Average, Students performing at this level demonstrate a developing command of the knowledge, skills, and practices embodied by the course at their grade level. The range for the grade of 4.0 is from 71% to 80% of the total possible score (100%).
4,5Above Average, Students performing at this level demonstrate a moderate command of the knowledge, skills, and practices embodied by the course. Students at this level are approaching the standards at their grade level. The range for the grade of 4.5 is from 81% to 90% of the total possible score (100%).
5,0Outstanding, Students performing at this level demonstrate a distinguished and strong command of the knowledge, skills, and practices embodied by the course. Students at this level are meeting or extending the standards at their grade level. The range for the grade of 5.0 is from 91% to 100% of the total possible score (100%).

Kryterium oceny - umiejętności

Efekt uczenia sięOcenaKryterium oceny
WM-WTMiT_1-_WM-WTMiT_U01
The ability to use the acquired knowledge to solve practical problems.
2,0Failing, Students performing at this level demonstrate no evidence of the knowledge, skills, and practices embodied by the course assessed at their grade level. The range for the grade of 2.0 is from 0% to 50% of the total possible score (100%).
3,0Acceptable, Students performing at this level demonstrate a minimal command of the knowledge and/or skills embodied by the course assessed at their grade level. The range for the grade of 3.0 is from 51% to 60% of the total possible score (100%).
3,5Below Average, Students performing at this level demonstrate a beginning command of the knowledge and/or skills embodied by the course assessed at their grade level. The range for the grade of 3.5 is from 61% to 70% of the total possible score (100%).
4,0Average, Students performing at this level demonstrate a developing command of the knowledge, skills, and practices embodied by the course at their grade level. The range for the grade of 4.0 is from 71% to 80% of the total possible score (100%).
4,5Above Average, Students performing at this level demonstrate a moderate command of the knowledge, skills, and practices embodied by the course. Students at this level are approaching the standards at their grade level. The range for the grade of 4.5 is from 81% to 90% of the total possible score (100%).
5,0Outstanding, Students performing at this level demonstrate a distinguished and strong command of the knowledge, skills, and practices embodied by the course. Students at this level are meeting or extending the standards at their grade level. The range for the grade of 5.0 is from 91% to 100% of the total possible score (100%).

Kryterium oceny - inne kompetencje społeczne i personalne

Efekt uczenia sięOcenaKryterium oceny
WM-WTMiT_1-_WM-WTMiT_K01
Improvement of social and personal competencies including self-awareness, self-management, social awareness, relationship skills, responsible decision-making and others. Encouraging dialogue and mutual respect between peoples of different nations, cultures and faiths.
2,0Students performing at this level demonstrate no evidence of increased social and emotional skills, improved attitude toward self and others, improved positive social behaviors, decreased conduct problems and emotional distress.
3,0Acceptable student's achivements in increased social and emotional skills, improved attitude toward self and others, improved positive social behaviors, decreased conduct problems and emotional distress.
3,5Below average student's achivements in increased social and emotional skills, improved attitude toward self and others, improved positive social behaviors, decreased conduct problems and emotional distress.
4,0Average student's achivements in increased social and emotional skills, improved attitude toward self and others, improved positive social behaviors, decreased conduct problems and emotional distress.
4,5Above average student's achivements in increased social and emotional skills, improved attitude toward self and others, improved positive social behaviors, decreased conduct problems and emotional distress.
5,0Oustending student's achivements in increased social and emotional skills, improved attitude toward self and others, improved positive social behaviors, decreased conduct problems and emotional distress.

Literatura podstawowa

  1. Grima P., Absolute Certainty and Other Fictions: The secrets of statistics, National Geographic, 2017, ISBN 978-84-473-8845-5
  2. Rumsey D.J., Statistics for Dummies, For Dummies, 2016, 2nd edition, ISBN 978-1119293521
  3. Rumsey D.J., Statistics II for Dummies, For Dummies, 2009, 1st edition, ISBN-13 978-0470466469
  4. EA, Expression of the Uncertainty of Measurement in Calibration, European co-operation for acreditation, 1999, EA-4/02
  5. NASA, Measurement Uncertainty Analysis Principles and Methods. NASA Measurement Quality Assurance Handbook – ANNEX 3, NASA, 2010, NASA Handbook, NASA-HDBK-8739.19-3
  6. Zilli M., A Practical Guide to the Calculation of Uncertainty of Measurement, The Open Toxicology Journal, 2013, 6, (Suppl 1, M3) 20-26, 2013
  7. Bell S., Measurement Good Practice Guide No. 11 (Issue 2). A Beginner’s Guide to Uncertainty of Measurement, National Physical Laboratory, Teddington, Middlesex, United Kingdom, 1999, ISSN 1368-6550
  8. Claus O. Wilke, Fundamentals of Data Visualization: A Primer on Making Informative and Compelling Figures, O'Reilly Media, 2019, 1st Edition, ISBN 978-1492031086
  9. Lydia Denworth, A Significant Problem, Scientific American, 2019, 10

Literatura dodatkowa

  1. Harper W.M., Statistics, Longman Group UK Ltd, 1991, 6th edition, ISBN 978-0712118996
  2. Volk B., Applied Statistics for Engineers, Krieger Pub Co., 1980, 2nd edition, ISBN 978-0898740714

Treści programowe - ćwiczenia audytoryjne

KODTreść programowaGodziny
T-A-1The solution of exercises related to issues discussed during lectures.28
T-A-2Skills evaluation.2
30

Treści programowe - wykłady

KODTreść programowaGodziny
T-W-1Elements of statistics: cases, variables, types of variables; matrix and frequency table; graphs and shapes of distributions; mode, median and mean; range, interquartile range and box plot, variance and standard deviation; Z-scores; contingency table, scatterplot, Pearson’s r; basics of regression; elementary probability; random variables and probability distributions (Normal Distribution, Binomial Distribution & Poisson Distribution).4
T-W-2Inferential statistics: observational studies and experiments; sample and population, population distribution, sample distribution and sampling distribution; Central Limit Theorem; point estimates, confidence intervals, introduction to hypothesis testing.4
T-W-3Measures of distribution shape: skewness and kurtosis. Skewness and kurtosis application to normality test.2
T-W-4How to use statistics to identify outliers in data (what are outliers and how to deal with them?): what are the outliers, types of outliers, most common causes of outliers on a data set (data entry errors(human errors), measurement errors (instrument errors), experimental errors (data extraction or experiment planning/executing errors), intentional (dummy outliers made to test detection methods), data processing errors (data manipulation or data set unintended mutations), sampling errors (extracting or mixing data from wrong or various sources), natural (not an error, novelties in data)).4
T-W-5Some of the most popular methods for outlier detection (Z-score or extreme value analysis, probabilistic and statistical modelling, linear regression models, proximity based models, information theory models, high dimensional outlier detection methods).4
T-W-6Evaluation of the uncertainty of measurement: measurant, uncertainty of measurement and measurement error, systematic and random errors (uncertainties), uncertainty of measurement and GUM terminology (Evaluation of Measurement Data - Guide to the Expression of uncertainty in measurement; usually referred to as the GUM), type a and type b uncertainties, degrees of freedom and uncertainty in the uncertainty, functional relationships, input and output quantities, propagation of uncertainty, uncertainty components when the inputs are uncorrelated, uncertainty components when the inputs are correlated, summary of procedure for determining the propagation of uncertainty, precision profile and uncertainty of measurement, rules for calculating uncertainty through functional relationships.4
T-W-7How people interpret data visualization and presentation. How to interpret uncertainty in common forms of data visualizations.2
T-W-8Statistical significance problem.2
T-W-9Final comment.2
T-W-10Evaluation of knowledge.2
30

Formy aktywności - ćwiczenia audytoryjne

KODForma aktywnościGodziny
A-A-1Class participation and active engagement for developing and refining students ability to critically and productively engage with the subjects being studied.30
A-A-2Preparation of homeworks and exercises.52
A-A-3Preparation to skills evaluation.5
87
(*) 1 punkt ECTS, odpowiada około 30 godzinom aktywności studenta

Formy aktywności - wykłady

KODForma aktywnościGodziny
A-W-1Participation in classes.30
A-W-2Self study.22
A-W-3Preparation to knowledge evaluation.10
62
(*) 1 punkt ECTS, odpowiada około 30 godzinom aktywności studenta
PoleKODZnaczenie kodu
Zamierzone efekty uczenia sięWM-WTMiT_1-_WM-WTMiT_W01To give relevant skills to presentation and analysis of collected data for research, commercial, industrial and marketing activities as well as professional practices. It helps in obtaining information from it as the raw data is non-comprehensive in nature.
Cel przedmiotuC-1To give relevant skills to presentation and analysis of collected data for research, commercial, industrial and marketing activities as well as professional practices.
Treści programoweT-W-1Elements of statistics: cases, variables, types of variables; matrix and frequency table; graphs and shapes of distributions; mode, median and mean; range, interquartile range and box plot, variance and standard deviation; Z-scores; contingency table, scatterplot, Pearson’s r; basics of regression; elementary probability; random variables and probability distributions (Normal Distribution, Binomial Distribution & Poisson Distribution).
T-W-5Some of the most popular methods for outlier detection (Z-score or extreme value analysis, probabilistic and statistical modelling, linear regression models, proximity based models, information theory models, high dimensional outlier detection methods).
T-W-9Final comment.
T-W-2Inferential statistics: observational studies and experiments; sample and population, population distribution, sample distribution and sampling distribution; Central Limit Theorem; point estimates, confidence intervals, introduction to hypothesis testing.
T-W-4How to use statistics to identify outliers in data (what are outliers and how to deal with them?): what are the outliers, types of outliers, most common causes of outliers on a data set (data entry errors(human errors), measurement errors (instrument errors), experimental errors (data extraction or experiment planning/executing errors), intentional (dummy outliers made to test detection methods), data processing errors (data manipulation or data set unintended mutations), sampling errors (extracting or mixing data from wrong or various sources), natural (not an error, novelties in data)).
T-W-3Measures of distribution shape: skewness and kurtosis. Skewness and kurtosis application to normality test.
T-W-7How people interpret data visualization and presentation. How to interpret uncertainty in common forms of data visualizations.
T-W-6Evaluation of the uncertainty of measurement: measurant, uncertainty of measurement and measurement error, systematic and random errors (uncertainties), uncertainty of measurement and GUM terminology (Evaluation of Measurement Data - Guide to the Expression of uncertainty in measurement; usually referred to as the GUM), type a and type b uncertainties, degrees of freedom and uncertainty in the uncertainty, functional relationships, input and output quantities, propagation of uncertainty, uncertainty components when the inputs are uncorrelated, uncertainty components when the inputs are correlated, summary of procedure for determining the propagation of uncertainty, precision profile and uncertainty of measurement, rules for calculating uncertainty through functional relationships.
Metody nauczaniaM-1Lectures
Sposób ocenyS-2Ocena podsumowująca: Students will be expected to complete written tests, projects and homework assignments as specified by the teacher.
S-1Ocena formująca: Student attendance and participation in class sessions play a vital role in successful course completion.
Kryteria ocenyOcenaKryterium oceny
2,0Failing, Students performing at this level demonstrate no evidence of the knowledge, skills, and practices embodied by the course assessed at their grade level. The range for the grade of 2.0 is from 0% to 50% of the total possible score (100%).
3,0Acceptable, Students performing at this level demonstrate a minimal command of the knowledge and/or skills embodied by the course assessed at their grade level. The range for the grade of 3.0 is from 51% to 60% of the total possible score (100%).
3,5Below Average, Students performing at this level demonstrate a beginning command of the knowledge and/or skills embodied by the course assessed at their grade level. The range for the grade of 3.5 is from 61% to 70% of the total possible score (100%).
4,0Average, Students performing at this level demonstrate a developing command of the knowledge, skills, and practices embodied by the course at their grade level. The range for the grade of 4.0 is from 71% to 80% of the total possible score (100%).
4,5Above Average, Students performing at this level demonstrate a moderate command of the knowledge, skills, and practices embodied by the course. Students at this level are approaching the standards at their grade level. The range for the grade of 4.5 is from 81% to 90% of the total possible score (100%).
5,0Outstanding, Students performing at this level demonstrate a distinguished and strong command of the knowledge, skills, and practices embodied by the course. Students at this level are meeting or extending the standards at their grade level. The range for the grade of 5.0 is from 91% to 100% of the total possible score (100%).
PoleKODZnaczenie kodu
Zamierzone efekty uczenia sięWM-WTMiT_1-_WM-WTMiT_U01The ability to use the acquired knowledge to solve practical problems.
Cel przedmiotuC-1To give relevant skills to presentation and analysis of collected data for research, commercial, industrial and marketing activities as well as professional practices.
Treści programoweT-A-1The solution of exercises related to issues discussed during lectures.
Metody nauczaniaM-2Exercises
Sposób ocenyS-2Ocena podsumowująca: Students will be expected to complete written tests, projects and homework assignments as specified by the teacher.
S-1Ocena formująca: Student attendance and participation in class sessions play a vital role in successful course completion.
Kryteria ocenyOcenaKryterium oceny
2,0Failing, Students performing at this level demonstrate no evidence of the knowledge, skills, and practices embodied by the course assessed at their grade level. The range for the grade of 2.0 is from 0% to 50% of the total possible score (100%).
3,0Acceptable, Students performing at this level demonstrate a minimal command of the knowledge and/or skills embodied by the course assessed at their grade level. The range for the grade of 3.0 is from 51% to 60% of the total possible score (100%).
3,5Below Average, Students performing at this level demonstrate a beginning command of the knowledge and/or skills embodied by the course assessed at their grade level. The range for the grade of 3.5 is from 61% to 70% of the total possible score (100%).
4,0Average, Students performing at this level demonstrate a developing command of the knowledge, skills, and practices embodied by the course at their grade level. The range for the grade of 4.0 is from 71% to 80% of the total possible score (100%).
4,5Above Average, Students performing at this level demonstrate a moderate command of the knowledge, skills, and practices embodied by the course. Students at this level are approaching the standards at their grade level. The range for the grade of 4.5 is from 81% to 90% of the total possible score (100%).
5,0Outstanding, Students performing at this level demonstrate a distinguished and strong command of the knowledge, skills, and practices embodied by the course. Students at this level are meeting or extending the standards at their grade level. The range for the grade of 5.0 is from 91% to 100% of the total possible score (100%).
PoleKODZnaczenie kodu
Zamierzone efekty uczenia sięWM-WTMiT_1-_WM-WTMiT_K01Improvement of social and personal competencies including self-awareness, self-management, social awareness, relationship skills, responsible decision-making and others. Encouraging dialogue and mutual respect between peoples of different nations, cultures and faiths.
Cel przedmiotuC-1To give relevant skills to presentation and analysis of collected data for research, commercial, industrial and marketing activities as well as professional practices.
Treści programoweT-A-1The solution of exercises related to issues discussed during lectures.
Metody nauczaniaM-2Exercises
M-1Lectures
Sposób ocenyS-2Ocena podsumowująca: Students will be expected to complete written tests, projects and homework assignments as specified by the teacher.
S-1Ocena formująca: Student attendance and participation in class sessions play a vital role in successful course completion.
Kryteria ocenyOcenaKryterium oceny
2,0Students performing at this level demonstrate no evidence of increased social and emotional skills, improved attitude toward self and others, improved positive social behaviors, decreased conduct problems and emotional distress.
3,0Acceptable student's achivements in increased social and emotional skills, improved attitude toward self and others, improved positive social behaviors, decreased conduct problems and emotional distress.
3,5Below average student's achivements in increased social and emotional skills, improved attitude toward self and others, improved positive social behaviors, decreased conduct problems and emotional distress.
4,0Average student's achivements in increased social and emotional skills, improved attitude toward self and others, improved positive social behaviors, decreased conduct problems and emotional distress.
4,5Above average student's achivements in increased social and emotional skills, improved attitude toward self and others, improved positive social behaviors, decreased conduct problems and emotional distress.
5,0Oustending student's achivements in increased social and emotional skills, improved attitude toward self and others, improved positive social behaviors, decreased conduct problems and emotional distress.