True or False: The higher the level of significance of a hypothesis test, the stronger the evidence we require to reject the null hypothesis.
True or False: The purpose of a hypothesis test is to assess the evidence in favour of the null hypothesis.
True or False: The higher the p-value of a hypothesis test, the more evidence we have to reject the null hypothesis.
1. The higher the level of significance of a hypothesis test, the stronger the evidence we require to reject the null hypothesis.
No, the higher is the level of significance, we require the higher p-value is required in order to accept the null hypothesis. The higher alpha we have, it becomes easier to reject the null hypothesis.
2. The purpose of a hypothesis test is to assess the evidence in favour of the null hypothesis.
Yes, that is the primary purpose of hypothesis testing, to test the statement of no effect i.e. the null hypothesis.
3. The higher the p-value of a hypothesis test, the more evidence we have to reject the null hypothesis.
Again, the higher the p-value, the stronger the evidence to accept the null hypothesis.
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