Draft
The purpose of the draft and peer review is to give you an opportunity to get early feedback on your analysis. Therefore, the draft and peer review will focus primarily on the exploratory data analysis, modeling, and initial interpretations.
Write the draft in the report.qmd
file in your project repo.
As you work on the draft, you should attempt to complete all the components of the final report, but it is okay to have some incompleteness or partial components. The focus should be on the analysis and less on crafting the final report. Your draft must include a reasonable attempt at each analysis component - data analysis, evaluation of significance, interpretation and conclusions.
Evaluation criteria
Category | Less developed projects | Typical projects | More developed projects |
Data description | Simple description of some aspects of the dataset, little consideration for sources. The description is missing answers to applicable questions detailed in the “Datasheets for Datasets” paper. |
Answers all relevant questions in the “Datasheets for Datasets” paper. | All expectations of typical projects + credits and values data sources. |
Data analysis | Analyses selected are not clearly purposeful. Preregistered analyses are not presented. |
Analyses selected are purposeful and further the data narrative, but questions raised are not adequately addressed. Preregistered analyses are presented. |
All expectations of typical projects + analyses are carefully selected to answer all reasonable questions. Questions raised by one analysis are addressed in subsequent analyses. |
Evaluation of significance | Metrics of statistical significance are present, but not interpreted for the reader and/or relevant to the analysis performed. | Metrics of statistical significance appropriate to the analysis performed are presented and are interpreted to some degree for the reader. | Metrics of statistical significance appropriate to the analysis performed are presented and clearly interpreted for the reader. Limitations of significance metrics are acknowledged. |
Interpretation and conclusions | Results are presented as numeric values and plots, with little to no written discussion. Values are printed out of context, with no/few labels. |
Values are interpreted in a way that is clear and addresses what the values mean and explain to some extent why they are important. Values are printed with clear labels. |
Interprets numeric values in a way that supports a clear story and conclusion creatively ties analysis together to present the results of the analysis through a well-written discussion. Values are presented in context and with clear labels. |