Here are the essential concepts you must grasp in order to answer the question correctly.
Null Hypothesis (H0)
The null hypothesis (H0) is a statement that indicates no effect or no difference, serving as a default position in statistical testing. In this context, it typically represents the status quo or a claim that a population parameter, such as the mean (μ), is equal to a specific value. For the given claim μ < 33, the null hypothesis would be H0: μ ≥ 33.
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Alternative Hypothesis (Ha)
The alternative hypothesis (Ha) is a statement that contradicts the null hypothesis, suggesting that there is an effect or a difference. It represents what the researcher aims to support through evidence. In this case, since the claim is μ < 33, the alternative hypothesis would be Ha: μ < 33, indicating that the population mean is indeed less than 33.
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Complement of a Hypothesis
The complement of a hypothesis refers to the opposite scenario of the original claim. In hypothesis testing, if the null hypothesis states that a parameter is greater than or equal to a certain value, its complement would assert that the parameter is less than that value. For the claim μ < 33, the complement would be μ ≥ 33, which aligns with the null hypothesis.
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