What are some common mistakes in data analysis?

What are some common mistakes in data analysis?

Some common mistakes include not cleaning data properly, ignoring outliers, and misinterpreting correlation as causation.

Can you explain why ignoring outliers is a mistake?

Ignoring outliers can skew your results and lead to incorrect conclusions. They can provide valuable insights.

What about sample size? How does it affect data analysis?

A small sample size can lead to unreliable results and increase the margin of error, making your findings less valid.

How can I avoid these mistakes in my analysis?

You can avoid these mistakes by thoroughly cleaning your data, using proper statistical methods, and validating your findings.