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The P Value
The P value is the universal measure that is used in hypothesis testing to determine whether to reject the Null hypothesis or fail to reject it. Each hypothesis test will calculate the appropriate P value based upon the test statistic.
When to use
P Values are associated with all hypothesis tests. If you are doing hypothesis testing, you will be using a P value.
The P Value is the probability that differences in your data are due to purely random effects. The P Value represents how well the statistical analysis supports the Null Hypothesis. Each hypothesis test will calculate the P value based upon the characteristics of the test calculations. In addition, the P value for a test can change based upon the size of the confidence interval, so the sample size and same standard deviation will impact the P value.
The P Value can range from 0 to 1.0. A P value threshold is set based upon the confidence level. The P threshold value is normally set to the alpha value. In most Lean Six Sigma projects the P threshold value is .05. Whenever the P value from the test is less than .05, the Null hypothesis is rejected. If the P value is greater than .05 the decision is to fail to reject the Null hypothesis.
The P value is the universal measure used with Lean Six Sigma hypothesis testing. Each test will calculate a P value based upon the results of the test. However, keep in mind, the P value is testing the Null hypothesis. The Null and Alternative hypotheses must be well-written for a Null hypothesis rejection to lead to an Alternative hypothesis acceptance.
Hints & tips
- The P value will always be based upon the Null hypothesis and the Null hypothesis is always supporting the position that there is nothing unusual about the data or samples.
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