Advanced statistical analysis tools including hypothesis testing and control charts tested on Six Sigma Black Belt exams, beyond the Green Belt DMAIC basics.
40 cards · basic cards · AI-written, checked twice. Edit anything.
- What is the difference between a Type I error and a Type II error?
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Type I is rejecting a true null hypothesis (false positive); Type II is failing to reject a false null hypothesis (false negative).- What is the primary purpose of a control chart in Six Sigma?
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To monitor a process over time and detect whether it is in statistical control or has gone out of control.- What is statistical power in hypothesis testing?
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The probability of correctly rejecting a false null hypothesis; the ability to detect a true effect, equal to 1 minus beta.- What is a p-value?
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The probability of observing data as extreme as or more extreme than what was observed, assuming the null hypothesis is true.- What does the alpha level (significance level) represent?
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The probability of making a Type I error; the threshold below which a p-value is considered statistically significant.- What is the difference between a one-tailed and a two-tailed hypothesis test?
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One-tailed tests for effect in one specific direction only; two-tailed tests for difference in either direction.- What does a Normal Probability Plot assess?
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Whether data follows a normal (Gaussian) distribution; points close to a straight line indicate normality.- What does a Gage R&R study measure?
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The amount of variation in a measurement system due to the equipment (repeatability) and different operators or conditions (reproducibility).- What does the capability index Cpk measure?
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How well a process can produce output within specification limits, accounting for centering; compares process variation to tolerance.- What is the difference between Cp and Cpk?
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Cp assumes the process is centered between specifications; Cpk accounts for actual process centering and is always less than or equal to Cp.- When should you use a non-parametric test instead of a parametric test?
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When data is not normally distributed, when sample size is very small, or when working with ranked or ordinal data.- What is stratification in data analysis?
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Dividing data into subgroups or strata based on a factor to reveal patterns that might be hidden in the overall data.- What is an interaction effect in an experiment?
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When the effect of one factor on the response depends on the level of another factor.- What is blocking in experimental design?
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Grouping experimental units into homogeneous blocks to reduce the effects of nuisance variables.- What does a main effects plot show?
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How the average response changes across different levels of each factor, graphically comparing factor impacts.
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