Hi there! Today, we’ll be talking about how exploratory data analysis (EDA) can help you answer important questions about your data.
First, let’s talk about how EDA can help you answer the question “Do I have the right data?” Imagine you’re trying to bake a cake, but you don’t have all the right ingredients. EDA is like checking to make sure you have all the ingredients you need before you start baking. By exploring your data, you can see what kind of information is available and whether it’s relevant to your analysis. You can also identify any missing data or errors that need to be addressed before you can move forward with your analysis.
Next, let’s talk about how EDA can help you determine which statistical tests are suitable for the data. Imagine you’re trying to figure out if a new medication is effective, but you’re not sure what kind of statistical test to use. By exploring your data, you can see what kind of variables you have and what kind of relationships exist between them, which can help you choose the most appropriate statistical tests for your analysis.
Data exploration can also help you determine what is worth following up on and what is not. Imagine you’re reading a book and trying to decide which characters are most important to the plot. Data exploration is like highlighting the most important parts of the book so you can focus on those when you’re trying to understand the story. By exploring your data, you can identify the most important variables and relationships, which can help you focus your analysis and identify the most important insights.
In conclusion, EDA is a powerful tool for exploring data and gaining insights into the patterns and relationships that exist within the data. By performing EDA, you can determine whether you have the right data, choose the most appropriate statistical tests for your analysis, determine what is worth following up on, and see the bigger picture of your data. So go forth and explore your data with EDA!