Project Guidelines

Writing Project Reports

Your reports can be made by extensive comments in the R script, by creating a markdown or composing a text document e.g. with word or pdf.

• add a short description of the datasets used in the project - use summary statistics to get an better overview
• shortly describe changes made to the single data set
• provide clear graphs which fit to your data, including descriptions

Evaluation Criteria

1. Data Cleaning, Preparation and Transformation

Correctness and completeness of data cleaning. Appropriateness of handling data inconsistencies. Successful merging of datasets. Accuracy and efficiency in transforming the data. Proper reshaping of data for analysis.

2. Effective and structured coding

Executable script without necessary corrections besides setting the working directory clear structure, fitting naming of objects, code with high reproducibility and low susceptibility to errors.

3. Data Visualization

Appropriateness of plots created. Customization and clarity of visualizations. Ability to highlight key trends and insights through visualizations.

4. Report and Presentation

Data sources — Origin of data clearly stated. Data overview — Time period, temporal/spatial resolution, and any gaps or quality issues reported Data transformations — Key processing steps documented concisely. Tone — Descriptive and precise. Conclusions — A clear, direct answer to the guiding question, discussion of results.

For more information or questions, please refer to the FAQ section or leave a comment below.