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Cursus: 201800031
201800031
Data Analysis in Water Engineering and Management
Cursus informatieRooster
Cursus201800031
Studiepunten (ECTS)5
CursustypeCursus
VoertaalEngels
Contactpersoonprof.dr. K.M. Wijnberg
E-mailk.m.wijnberg@utwente.nl
Docenten
Docent
ir. M. Teixeira Manion
Docent
prof.dr. K.M. Wijnberg
Contactpersoon van de cursus
prof.dr. K.M. Wijnberg
Collegejaar2021
Aanvangsblok
1B
AanmeldingsprocedureZelf aanmelden via OSIRIS Student
Inschrijven via OSIRISJa
Cursusdoelen
After this course, the student is able to:
  • Critically evaluate the quality of a data set and deal with any peculiarities (outliers, missing data, etc.) in a sound way;
  • Evaluate on and use the relevant data analysis technique for given combinations of data set and question;
  • Apply (at non-expert level) several common data analysis techniques for dealing with time series, spatial data, and multivariate data;
  • Interpret and discuss the results of the selected set of analysis techniques, taking the limitations of the data set into account;
  • Present and elaborate on the results of a data investigation in a clear and transparent manner.
Inhoud
Observational data are an important source of information for understanding and predicting the behaviour of water systems. Monitoring the state of water systems is becoming an increasingly wide-spread practice. Hence large datasets become widely available to benefit the management of these water systems.
 
To extract information from data, a wide variety of analysis techniques and tools are available, each with its own merits and drawbacks. This course treats a selection of techniques commonly used in the field of water engineering and management. Since real world data sets tend to be imperfect (missing data, outliers), and the professional reality is that you have to select the most appropriate analysis method yourself, this course will also teach you a general strategy on how to properly perform a data investigation and interpret the results in a sound way.
The extent to which the student has achieved the learning objectives of the course is assessed by means of an assignment and a written exam at the end of the quartile.

Is knowledge of programming skills necessary for this course? Please specify the skills / knowledge of which programme(s) is / are needed.
Basic skills in Matlab programming are needed, The core of matlab scripts that are needed in the various exercises and the assignment are provided, but these scripts need to be understood and modified individually by the student.
Voorkennis
Prior knowledge necessary: introductory level statistics course, basic skills in Matlab programming (or similar programming language).
Participating study
Master Civil Engineering and Management
Verplicht materiaal
Boek
"Statistics and data analysis in geology", J.C. Davis, 3rd edition, John Wiley & Sons, ISBN 0-471-17275-8.
Canvas
Various hand-outs and journal papers made available through Canvas
Aanbevolen materiaal
-
Werkvormen
Assignment
AanwezigheidsplichtJa

Lecture
AanwezigheidsplichtJa

Other

Practical
AanwezigheidsplichtJa

Q&A

Self study without assistance

Toetsen
Written examination & (group) assignment

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