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 in the sample data to reject H0 in favor of Ha.
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Critical Value and Rejection Region
The critical value is a threshold that determines the boundary for rejecting the null hypothesis in hypothesis testing. It is derived from the significance level (α), which indicates the probability of making a Type I error. The rejection region is the range of values for the test statistic that leads to the rejection of H0. If the calculated test statistic falls within this region, we reject the null hypothesis.
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Standard Deviation and Chi-Square Test
The standard deviation is a measure of the amount of variation or dispersion in a set of values. In the context of hypothesis testing for standard deviation, the Chi-Square test is used to determine if the sample standard deviation significantly differs from a hypothesized population standard deviation. The test statistic is calculated using the sample data, and its value is compared to the critical value to make a decision regarding the null hypothesis.
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