two quick questions
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1. Explain when a z-test would be appropriate over a t-test.
2. Researchers routinely choose an alpha level of 0.05 for testing their hypotheses. What are some experiments for which you might want a lower alpha level (e.g., 0.01)? What are some situations in which you might accept a higher level (e.g., 0.1)?
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- Explain when a z-test would be appropriate over a t-test
ANSWER
Both z and t tests are key functions used in statistical evaluation of hypotheses. In the event of research, part of data analysis requires the approximation of the normal distribution. Nonetheless, the critical levels of both tests makes the huge disparity between them. This assertion is based on the fact that critical levels are used to determine the point of accuracy of the midpoint or central limit. Therefore, in a research a student is more likely to consider the t test as it offers separated critical value for each sample rather than z test that offers a single one.
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