Transforming Data: The Basics (Video)

Here we cover how to transform one variable into another. This is a common task in data sciences and an essential skill for any data analyst or researcher. Transformations can help you uncover hidden patterns, meet statistical assumptions, or simply make your data more interpretable.

As you get your data ready for analysis, start thinking about what you want to achieve and what questions you’re trying to answer. The transformation you choose should align with your research goals and the nature of your data. Remember, the right transformation can make complex relationships more apparent and can significantly improve the quality of your analysis.

In the video we cover the following:

• Transforming variables: We’ll explore why and when you might need to transform your data. This includes scenarios like standardising your and handling outliers.
• Types of transformations: We’ll discuss various transformation techniques, turning continuous variables into ordinal ones or how to standardise a variable.
• Errors to avoid: We’ll highlight common pitfalls in data transformation, such as applying the wrong type of transformation, forgetting to back-transform results, or transforming variables unnecessarily.
• Practical examples: We’ll walk through real-world examples of data transformation, demonstrating how to apply these techniques using popular statistical software.

At the end of the session, you will be able to confidently transform data and create new variables that you can use in your analysis moving forward. You’ll understand not just how to perform transformations, but also why they’re necessary. This skill will enable you to handle a wider range of datasets and extract more meaningful insights from your data.

Remember, use transformations sparingly. Always consider the implications of transforming your data and ensure that any transformations you apply are appropriate for your specific research context.