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 change or no effect, serving as a default position that there is no relationship between variables. 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 question, H0 would state that the population proportion p is equal to 0.21, while Ha would state that p is not equal to 0.21.
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Complement of a Hypothesis
The complement of a hypothesis refers to the opposite of the original statement. In hypothesis testing, if the null hypothesis states a specific value (e.g., p = 0.21), the complement would encompass all other possibilities (e.g., p ≠ 0.21). Understanding the complement is crucial for correctly formulating the alternative hypothesis and interpreting the results of the hypothesis test.
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