Measure Phase: Data Analysis Flashcards
7 cards from real Lean Six Sigma Black Belt Certification practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 7 Measure Phase: Data Analysis flashcards as text
A Gauge R&R study reveals that %Gauge R&R is 28%. How should this measurement system be classified?
Answer: Marginal—acceptable depending on application and customer approval
A %Gauge R&R between 10% and 30% is considered marginal; it may be acceptable depending on the importance of the application and cost of repair.
What is the relationship between Type I error (alpha) and Type II error (beta) when sample size is fixed?
Answer: Reducing alpha increases beta (they have an inverse relationship)
With a fixed sample size, decreasing alpha (the risk of a false positive) increases beta (the risk of a false negative) because the decision boundary shifts.
In a Box-Cox transformation, what is the goal?
Answer: To stabilize variance and make non-normal data approximately normal
The Box-Cox transformation applies a power function to non-normal data to stabilize variance and achieve approximate normality for parametric analysis.
Which statistic is used to assess the overall adequacy of a multiple regression model?
Answer: Adjusted R-squared
Adjusted R-squared measures the proportion of variance explained by the model while penalizing for adding unnecessary predictors, making it suitable for comparing models.
A process produces 340 defects per million opportunities (DPMO). What sigma level does this correspond to approximately?
Answer: 5 sigma
A DPMO of approximately 233 corresponds to 5 sigma; 340 DPMO is very close to the 5-sigma level using the 1.5-sigma shift convention.
What does the Anderson-Darling test evaluate in data analysis?
Answer: Whether a dataset follows a specified distribution (typically normal)
The Anderson-Darling test is a goodness-of-fit test that assesses whether sample data come from a specified distribution such as the normal distribution.
In a time-series analysis, which component represents the long-term upward or downward movement in data?
Answer: Trend
The trend component in time-series analysis represents the long-term, sustained upward or downward movement in a dataset over time.