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 default position, and the alternative hypothesis (H1), which represents a new claim. The goal is to determine whether there is enough evidence to reject the null hypothesis in favor of the alternative.
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Null and Alternative Hypotheses
In hypothesis testing, the null hypothesis (H0) is a statement that there is no effect or no difference, and it serves as the starting point for the test. The alternative hypothesis (H1) is what the researcher aims to support, suggesting that there is an effect or a difference. It is crucial to understand that during the testing process, we assume the null hypothesis is true until evidence suggests otherwise.
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Assumption in Hypothesis Testing
In hypothesis testing, the assumption is that the null hypothesis is true at the beginning of the test. This means that the evidence collected from the sample data is used to evaluate whether there is sufficient support to reject the null hypothesis. The statement in the question is false because we do not assume the alternative hypothesis is true; rather, we start with the null hypothesis.
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