Data cleaning is an essential and time-consuming part of statistical analysis. The purpose of data cleaning is to prepare datasets and variables for analysis, visualization, and/or statistical model building. It is necessary to ensure that spreadsheets are organized with valid values and manageable variables. This lecture covers best practices for organizing spreadsheets and provides basic tips for data cleaning. The goal is to achieve "organized data," which will make downstream analysis more efficient, make the data machine-readable, and contribute to making research reproducible.
The webinar will go over common errors and provide concrete examples of good practices. We will evaluate sample data, and there will be an opportunity for questions and discussion.
This webinar is based on the module "How to structure and document research data."
And you may also be interested in one of our other thematic webinars, such as "How to use an electronic lab notebook." For more information, please refer to our Course Calendar.
For more information on research data management at UiT, please visit the UiT Research Data Portal.