beta error

Beta error, also called a Type II error, occurs when a statistical test fails to detect a real effect or difference that actually exists. In simple terms, it’s like missing a true positive signal. For example, if a medical test should identify people with a condition but misses some cases, that reflects a beta error. It’s influenced by factors like sample size and test sensitivity. Reducing beta error helps improve the chances of detecting real effects or differences when they are present, making the conclusions more reliable.