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Updated in [July 27th, 2023]
This course provides a comprehensive guide to help new learners understand the importance of data cleaning and preparing data for accurate analyses. It is designed to give step-by-step examples for everything from anticipating data cleaning needs to determining what to do with missing data. PowerPoint slides and other helpful supporting materials are provided to aid in practice or for one's own data project. It is suitable for doctoral students, undergraduate students, early career researchers, and those who wish to learn about the process of conducting rigorous research studies. The course also offers insight into anticipating cleaning before or during collection, understanding why not all missing data are the same, the importance of recording the cleaning process and decisions, and what part of cleaning to report in a manuscript.
Course Syllabus
Introduction
Module 1 - Early Considerations Prior to Cleaning
Module 2 - Cleaning Preparation and the Cleaning Process
Module 3 - Effects of Missing Data and Reporting the Cleaning Process
Bonus Content