解释null和alternative假设的区别，并说明如何建立这两种假设

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∻Solution by Steps∻ ‖ step 1 ⋮ Null hypothesis (H₀) is a statement that there is no effect or no difference, while the alternative hypothesis (H₁) is what you want to prove, indicating that there is an effect or a difference. ‖ ‖ step 2 ⋮ To establish the null hypothesis, you typically state it in a way that reflects no change or no relationship, such as $ H_0: \mu = \mu_0 $, where $ \mu_0 $ is a specific value. ‖ ‖ step 3 ⋮ The alternative hypothesis is formulated to reflect the opposite of the null hypothesis, such as $ H_1: \mu \neq \mu_0 $ for a two-tailed test, indicating that the mean is different from $ \mu_0 $. ‖ ∻Answer∻ ⚹ The null hypothesis states no effect, while the alternative hypothesis indicates an effect. Establish them by defining a specific value for the null and its opposite for the alternative. ⚹ ∻Key Concept∻ ⚹ Null and alternative hypotheses are fundamental in hypothesis testing. ⚹ ∻Explanation∻ ⚹ The null hypothesis represents a default position, while the alternative hypothesis represents what you aim to support through your data analysis. ⚹◊在统计检验中，如何选择适当的显著性水平 $\alpha$ 来进行假设检验？⍭ Generate me a similar question◊

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