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Data cleaning, or data preparation is an essential and time-consuming part of statistical analysis. Before you can analyse your data you must make sure your spreadsheets are well organised with valid entries and manageable variables. This lecture will cover the best practices for organising spreadsheets and the basics of cleaning data to make the data “tidy”. Tidy data will dramatically speed downstream data analysis tasks, make the data machine-readable, and contribute to make the research reproducible.
We will evaluate and discuss example data with typical mistakes and demonstrate best practices. There will be time for questions and discussion.
The webinar builds on the module “How to structure and document research data”.
For more information about research data management at UiT, see the UiT Research Data Portal.