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Six Sigma Study Guide

Six Sigma Study Guide

Study notes and guides for Six Sigma certification tests
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Home  /  Six Sigma Study Guide Articles  /  Author: Ted Hessing

Author: Ramana PV

Ted Hessing

Poisson Distribution

Posted by Ted Hessing

Poisson distribution is a discrete probability distribution; it describes the mean number of events occurring in a fixed time interval.

This entry was posted in Advanced Data Distributions, Measure and tagged ASQ, Black Belt, Green Belt, QuestionSet, Villanova. Bookmark the permalink.
Ted Hessing

Chi Square Distribution & Hypothesis Test

Posted by Ted Hessing

The chi square (χ2) distribution is the best method to test a population variance against a known or assumed value of the population variance

This entry was posted in Advanced Data Distributions, Analyze, Measure, Performing Hypothesis Tests with Non Normal Data and tagged ASQ, Black Belt, Breakup, Download, Green Belt, IASSC, QuestionSet, Villanova. Bookmark the permalink.
Ted Hessing

Data Distributions

Posted by Ted Hessing

Data distributions is a function that specifies all possible values for a variable and also quantifies the relative frequency.

This entry was posted in Basic Data Distributions, Measure and tagged ASQ, Black Belt, Green Belt, IASSC, Villanova. Bookmark the permalink.
Ted Hessing

Central Tendency

Posted by Ted Hessing

Central tendency is the idea that when using normal data, all three of the main measures (mean, mode, median) tend to be roughly the same.

This entry was posted in Descriptive Statistics, Measure and tagged ASQ, Black Belt, Green Belt, IASSC, Villanova. Bookmark the permalink.
Ted Hessing

Standard Deviation

Posted by Ted Hessing

Standard deviation is the measure of variation in a process. Describing variation by standard deviations lets us easily compare processes.

This entry was posted in Measure and tagged ASQ, Black Belt, Green Belt, IASSC, Villanova. Bookmark the permalink.
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