When testing the difference of means for paired data, which of the following is the correct null hypothesis?
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Understand that in hypothesis testing for paired data, we are interested in the mean difference \( \mu \) between the paired observations.
The null hypothesis \( H_0 \) typically states that there is no difference in means, which means the mean difference \( \mu \) is equal to zero.
Formally, the null hypothesis is written as:
\[ H_0: \mu = 0 \]
The alternative hypothesis \( H_a \) can take different forms depending on the research question: it could be \( \mu \neq 0 \) (two-tailed), \( \mu > 0 \) (right-tailed), or \( \mu < 0 \) (left-tailed).
Therefore, the correct null hypothesis for testing the difference of means in paired data is that the mean difference is zero, which corresponds to \( H_0: \mu = 0 \).