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Data
Cross-sectional data
Description and assignment for first project phase:
- Data understanding: read the documentation, go through the data; describe necessity for data cleaning, integration, missing values
- Data description: describe the data set; use short textual description and descriptive statistics
- Analysis questions: formulate two analysis questions that you would be interested about based on the data
- First report: Generate a project and data repository in R. Use rmarkdown and knitr for documentation
Deliverables first project phase (9 points):
** data description including requirements for cleaning and integration; descriptive statistics (plots!) on the data (3 points)
** two analysis questions with description (4 points)
** Presentation using rmarkdown and knitr (2 points)
Description and assignment for second project phase:
** Refine the two original analysis questions based on discussion during first project presentation
** Conduct different analysis techniques in order to answer the refined analysis questions
** Definition of two follow-up questions
Deliverables second project phase (9 points):
** Two refined analysis questions (2 points)
** Analysis results (5 points)
** Two follow-up questions (2 points)
** The analysis results should be formulated as an excutive summary (app. 5. pages) which supports decison makers in their future actions
Business process logs
(doi:10.4121/uuid:d9769f3d-0ab0-4fb8-803b-0d1120ffcf54) |
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(doi:10.4121/uuid:3926db30-f712-4394-aebc-75976070e91f) |
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(doi:10.4121/uuid:a7ce5c55-03a7-4583-b855-98b86e1a2b07) |
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(doi:10.4121/uuid:c3e5d162-0cfd-4bb0-bd82-af5268819c35) |
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(doi:10.4121/uuid:31a308ef-c844-48da-948c-305d167a0ec1) |
Description and assignment for first project phase:
- Data understanding: read the documentation, go through the data; describe necessity for data cleaning, integration
- Data description: describe the data set; use short textual description and descriptive statistics
- Analysis questions: formulate two analysis questions that you would be interested about based on the data
- First analysis: apply the following process mining techniques to the data: Heuristics Miner, Mining a Petri Net
- Tool: «ProM»
Deliverables first project phase (9 points):
** data description including requirements for cleaning and integration; descriptive statistics (plots!) on the data (3 points)
** two analysis questions with description (4 points)
** one Petri Net model, one Heuristic Net; both produced by applying the associated process mining technique on the data set using ProM (2 points)
Description and assignment for second project phase:
** Refine the two original analysis questions based on discussion during first project presentation
** Conduct different analysis techniques in order to answer the refined analysis questions
** Definition of two follow-up questions
Deliverables second project phase (9 points):
** Two refined analysis questions (2 points)
** Analysis results (5 points)
** Two follow-up questions (2 points)
Text mining
Description and assignment for first project phase:
- Data understanding: read the documentation about text mining, go through the data (build the dataset);
- Data description: build a document-term matrix and describe the data set; use short textual description and descriptive statistics
- Analysis questions: apply different basic operations and formulate two analysis questions that you would be interested about the texts
- First report: Generate a corpus and document the work using rmarkdown and knitr
Deliverables first project phase (9 points):
** data description including requirements for cleaning and integration; descriptive statistics (plots!) on the data (3 points)
** two analysis questions with description (4 points)
** Presentation using rmarkdown and knitr (2 points)
Description and assignment for second project phase:
** Refine the two original analysis questions based on discussion during first project presentation
** Conduct different analysis techniques in order to answer the refined analysis questions
** Definition of two follow-up questions
Deliverables second project phase (9 points):
** Two refined analysis questions (2 points)
** Analysis results (5 points)
** Two follow-up questions (2 points)
** The analysis results should be formulated as an excutive summary (app. 5. pages) which explains main characteristics of the corpus
Tools
Last Change: 04.11.2016, 11:47 | 624 Words