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The p of 0.05 is the value at which most draw the line in accepting or rejecting the null in hypothesis testing. However, it's important to remember that a p of 0.05 means that there is still the possibility of making a false assertion five percent of the time. This misconception can cost the reliability of hypothesis testing in some Six Sigma Projects.

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By definition, hypothesis testing is being able to determine whether one group of data is different from another. The null hypothesis is key to this process as it always states that the variables under study in the hypothesis testing makes no difference. This puts the burden on those testing the data to find another way to prove that the variables do make a difference. If users reject the null, the variables do indeed make a difference in the outcome measures, which is generally the goal of the Six Sigma project.

When rejecting the null hypothesis, there's more that should be considered than the p-value. While this value is generally a reliable number, five percent is certainly not zero percent.