What is statistical significance and why is it important?

What is statistical significance and why is it important?

Statistical significance is a measure that helps determine if the results of a study are likely due to chance or if they reflect a true effect. It's important because it helps researchers make informed decisions based on data.

How do you determine if a result is statistically significant?

To determine statistical significance, researchers typically use a p-value. A p-value less than 0.05 is commonly considered significant, indicating that there's less than a 5% probability that the observed results happened by chance.

What does a p-value of 0.01 mean?

A p-value of 0.01 means there's only a 1% chance that the observed results are due to random variation. This suggests strong evidence against the null hypothesis.

Can you explain the difference between statistical significance and practical significance?

Yes! Statistical significance indicates whether an effect exists, while practical significance assesses whether the effect is meaningful in real-world applications.

What are some common misconceptions about statistical significance?

Common misconceptions include thinking that a statistically significant result is always practically important, or that a non-significant result means there's no effect at all.