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Module 3: Cleaning Data
This course provides a foundational understanding of how to clean and automate data in R, in order to analyse and interpret data more effectively. Benjamin will emphasise the practical applications of cleaning and automating data in a sports science context. Throughout the lessons, you will gain valuable insights into:
- Importance of Data Cleaning: Highlights the necessity of cleaning data for accurate and reliable analysis in sports science.
- Handling Common Data Issues: Covers strategies for dealing with outliers, missing values, duplicates, and inconsistent data entries.
- Automation and Practical Applications: Emphasises automating data cleaning tasks to save time and improve efficiency.
- Methods and Tools: Introduces statistical and visual tools to identify and address data problems, such as IQR and Z-scores.
Upon completing this course, you will have a general understanding of how to automate data processes and ensure clean data in your practice.
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