Hypothesis testing is a fundamental Six Sigma tool used to make data-driven decisions by evaluating assumptions about a population parameter. It involves formulating a null hypothesis (H0) and an alternative hypothesis (H1). The null hypothesis represents a statement of no effect or no difference, while the alternative hypothesis represents the effect or difference you aim to detect. Statistical tests, such as t-tests or chi-square tests, are used to analyze sample data and determine whether to reject the null hypothesis. Hypothesis testing helps validate improvements, compare processes, and ensure that observed changes are statistically significant, driving informed decisions and process optimization.
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