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Project Management · Six Sigma Black Belt

Six Sigma Black Belt: Statistical Tools

Advanced statistical analysis tools including hypothesis testing and control charts tested on Six Sigma Black Belt exams, beyond the Green Belt DMAIC basics.

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What is the difference between a Type I error and a Type II error?
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?
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?
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?
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?
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?
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?
Whether data follows a normal (Gaussian) distribution; points close to a straight line indicate normality.
What does a Gage R&R study measure?
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?
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?
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?
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?
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?
When the effect of one factor on the response depends on the level of another factor.
What is blocking in experimental design?
Grouping experimental units into homogeneous blocks to reduce the effects of nuisance variables.
What does a main effects plot show?
How the average response changes across different levels of each factor, graphically comparing factor impacts.

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