Statistical error analysis is a crucial component of interpreting data rightly. Understanding the potential errors in your data can significantly impact how you apply your insights in real-world scenarios.
There are two primary types of statistical errors:
- Type I Error: Incorrectly rejecting a true null hypothesis.
- Type II Error: Failing to reject a false null hypothesis.
To delve deeper, the Community has extensive resources and practical examples to explore.
