What are common statistical mistakes?

What are some common mistakes people make when interpreting statistics?

Some common mistakes include confusing correlation with causation, ignoring sample size, and misinterpreting p-values.

Can you explain why correlation does not imply causation?

Sure! Correlation means two variables move together, but it doesn't mean one causes the other. There could be other factors involved.

What about sample size? How does it affect statistical results?

A small sample size can lead to unreliable results and increase the margin of error, making it hard to generalize findings.

What is a p-value and why is it often misunderstood?

A p-value measures the probability of observing results as extreme as the data, given that the null hypothesis is true. It's often misinterpreted as the probability that the null hypothesis is true.

How can I avoid these mistakes in my analysis?

To avoid these mistakes, ensure you understand the data context, use appropriate sample sizes, and consult statistical guidelines.