Here are the essential concepts you must grasp in order to answer the question correctly.
Hypothesis Testing
Hypothesis testing is a statistical method used to make decisions about a population based on sample data. It involves formulating two competing hypotheses: the null hypothesis (H0), which represents a statement of no effect or no difference, and the alternative hypothesis (Ha), which represents the claim being tested. The goal is to determine whether there is enough evidence to reject H0 in favor of Ha.
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Null and Alternative Hypotheses
The null hypothesis (H0) is a statement that indicates no significant effect or relationship exists in the population, serving as a baseline for comparison. The alternative hypothesis (Ha) is the statement that reflects the claim or effect that the researcher aims to support. In the context of the given statement, H0 would be σ^2 < 1.2, while Ha would be σ^2 ≥ 1.2.
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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 original claim is that a parameter is greater than or equal to a certain value, its complement would state that the parameter is less than that value. This is crucial for defining the null hypothesis, as it allows for a clear distinction between what is being tested and what is assumed to be true under the null.
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