Glossary Terms Archive

Beta Risk (Type II Error): Definition, Formula, and Six Sigma Examples

Beta risk (β) is the probability of failing to detect a real difference or effect that actually exists in a process. In hypothesis testing, beta risk occurs when a team concludes that no significant difference exists, when in fact one does. It is also called a Type II...

Bartlett’s Test for Homogeneity of Variances

Bartlett’s test encompasses several related statistical procedures designed to examine variance characteristics in datasets. Originally developed by Maurice Bartlett in the 1930s and 1940s, these tests have become essential tools in modern statistical analysis....

Average in Six Sigma: Arithmetic Mean, Types, Formula, and DMAIC Applications

An average is a single value that represents the center of a dataset. It summarizes a group of numbers into one number that is most representative of the whole. In Six Sigma, the average is one of the first statistics calculated in the Measure phase of DMAIC. It tells...

Alternative Hypothesis

In statistical analysis, hypothesis testing plays a critical role in making data-driven decisions. The process typically involves testing two mutually exclusive hypotheses: the null hypothesis (H0) and the alternative hypothesis (H1). This distinction helps...

Alpha Risk in Six Sigma: What It Is and Why It Matters

Imagine your team runs a hypothesis test and the data says: the improvement worked. Defect rates are down. The result is statistically significant. Everyone is ready to celebrate. But there is a question worth asking before you do: what if the data is wrong? Not...