Hypothesis testing, why alpha cannot be zero

In summary, hypothesis testing is a statistical method used to determine whether a proposed hypothesis about a population is supported by a sample of data. Alpha (α) is important in hypothesis testing because it helps us set a threshold for how much evidence is needed to reject the null hypothesis. Setting alpha (α) to zero would make it nearly impossible to reject the null hypothesis and draw meaningful conclusions from the data. Alpha (α) cannot be set to zero in hypothesis testing as it would violate basic principles and lead to incorrect conclusions. The appropriate value for alpha (α) is typically chosen before conducting the experiment and should be based on the desired level of risk and context of the research.
  • #1
Deathfish
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Ok someone tell me the official explanation of why alpha cannot be zero in hypothesis testing.
 
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  • #2
The UNOFFICIAL explanation (I don't know who could give you the "official" explanation) is that, if you set alpha to zero, you will always accept your null hypothesis, and thus hypothesis testing would be pointless.

Think about it. Testing at P < 0 means that you will call significant only a result that has probability less than 0 of happening if the null hypothesis is true. Obviously, there is never such a result.
 

FAQ: Hypothesis testing, why alpha cannot be zero

1. What is hypothesis testing?

Hypothesis testing is a statistical method used to determine whether there is enough evidence to reject or accept a proposed hypothesis about a population based on a sample of data.

2. Why is alpha (α) important in hypothesis testing?

Alpha (α) is the level of significance used in hypothesis testing to determine the probability of making a type I error, which is rejecting a true null hypothesis. It helps us set a threshold for how much evidence we need to reject the null hypothesis.

3. What happens if alpha (α) is set to zero in hypothesis testing?

If alpha (α) is set to zero, it means that we are not willing to accept any risk of making a type I error. This would make it nearly impossible to reject the null hypothesis and would not allow for any meaningful conclusions to be drawn from the data.

4. Can alpha (α) ever be set to a value of zero in hypothesis testing?

No, alpha (α) cannot be set to a value of zero in hypothesis testing. This would violate the basic principles of hypothesis testing and would lead to incorrect conclusions being drawn from the data.

5. How do we choose the appropriate value for alpha (α) in hypothesis testing?

The appropriate value for alpha (α) in hypothesis testing is typically chosen before conducting the experiment or analyzing the data. It should be based on the desired level of risk for making a type I error and the context of the research being conducted.

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