Inferential Statistics is largely about Significance. There are both Practical and _______________ Significance to consider during an analysis of data in a Lean Six Sigma project.

In the context of Lean Six Sigma and inferential statistics, analysis requires evaluating two distinct types of significance. Statistical significance indicates if an observed effect in the data is unlikely to have occurred by random chance. This is typically assessed using p-values from hypothesis tests. Practical significance, in contrast, evaluates whether the magnitude of the effect is large enough to be meaningful, valuable, or useful in a real-world business application. A statistically significant result might not be practically significant if the effect size is too small to justify implementation costs or to have a noticeable impact on performance. Both must be considered for effective decision-making.

A. Problematic: This is a general adjective and not a recognized term for a type of significance in statistical analysis.
B. Impractical: This describes the absence of practical significance, rather than being the complementary type of significance to it.
C. Usable: This is a synonym for 'practical' and does not represent the formal statistical concept that is contrasted with practical significance.

1. The Pennsylvania State University. (n.d.). STAT 500: Applied Statistics, Lesson 6.1.2 - Practical Significance vs. Statistical Significance. Eberly College of Science. Retrieved from https://online.stat.psu.edu/stat500/lesson/6/6.1/6.1.2. In this section, the courseware explicitly states, "Statistical significance is concerned with whether an observed effect is due to chance. Practical significance is concerned with whether the observed effect is large enough to be useful in the real world."

2. Wasserstein, R. L., & Lazar, N. A. (2016). The ASA's Statement on p-Values: Context, Process, and Purpose. The American Statistician, 70(2), 129–133. https://doi.org/10.1080/00031305.2016.1154108. Principle 5 (p. 132) states, "A p-value, or statistical significance, does not measure the size of an effect or the importance of a result," thereby distinguishing statistical significance from practical importance (significance).