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Hypothesis Testing

A hypothesis test consists of two complementary propositions. For example, suppose that the test is to see if a process mean differs from zero:

H0 the mean equals zero (this is the 'null hypothesis')
H1 the mean does not equal zero (this is the 'alternative hypothesis')

The test will determine the probability of getting the observed results if H0 were true. This probability is known as the p-value.

Terms used in hypothesis testing include:

 Alpha Risk Power of a Test Alpha Value (Significance Level) P-value Beta Risk Statistical v Practical Significance Single/Double Sided Test Type I & Type II Errors Hypothesis testing is covered in the MiC Quality Advanced Statistics Course. Try out our courses by taking the first module of the Primer in Statistics free of charge. [SIX SIGMA GLOSSARY ALPHABETICAL INDEX] [SIX SIGMA GLOSSARY INDEX OF TOPICS] [Top]

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