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Alpha is the significance level of the test and has little to do with the failure rate of parts (or even parst!).

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What does it mean if you have α equal to 0.05 and you will check 100 consecutive parts?

If you have an α (alpha) level of 0.05, it means you are willing to accept a 5% chance of committing a Type I error, which is rejecting a true null hypothesis. When testing 100 consecutive parts, the likelihood of encountering at least one false positive increases due to multiple comparisons. Specifically, the probability of observing at least one false positive can be calculated using the formula (1 - (1 - \alpha)^n), which in this case would be approximately 99.5%. This highlights the importance of adjusting your significance threshold or employing methods like the Bonferroni correction to account for multiple testing.


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From a probability perspective fair means equal probability.


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One is a measure of probability, the other is a measure of width! And neither is the same as equal age, or equal loudness!One is a measure of probability, the other is a measure of width! And neither is the same as equal age, or equal loudness!One is a measure of probability, the other is a measure of width! And neither is the same as equal age, or equal loudness!One is a measure of probability, the other is a measure of width! And neither is the same as equal age, or equal loudness!


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