Type I errors are always worse to make than Type II errors.
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Retaining H0 and accepting H0 mean the same thing.
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The critical probability for rejecting H0 is the alpha level.
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If we reject H0 then we are absolutely certain the independent variable affected the dependent variable.
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If we reject H0 one can say the experimental results are significant.
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It is not possible to analyze the probability of the alternative hypothesis because the laws of probability are derived for chance events. This is why we test H0 instead of H1.
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H0 always asserts that the dependent variable has no effect on the independent variable.
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H0 and H1 must be mutually exclusive and exhaustive.
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The statement Drug X has no effect on Y and any observed effect is due to chance alone is an example of a nondirectional alternative hypothesis.
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Unless the very same subject is used in the control and experimental condition the design cannot be a replicated measures design.
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