Topic 5 DQ1 -Response 1 & 2
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Topic 5 DQ 1-Response 1 & 2
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May 2023
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Topic 5 DQ 1 Response 1 & 2
Explain how the level of significance and sample size influence hypothesis testing results.
Provide an example and explain how they might impact business decisions. Be sure to give
references.
In reply to your peers, discuss whether you agree or disagree with the example provided, justify
your response, and use reference source(s) to support your response. Explain some ethical
considerations when dealing with level of significance and sample size.
Reply to Taylor Mitchell
Hello Taylor Mitchell,
Thank you for sharing your perspective with us. In response to your post, I both agree and
respectfully disagree with certain aspects. While it is true that a higher sample size can increase
the significance level of the findings, it is important to note that the significance level itself is
determined by the researcher before conducting the experiment. The significance level represents
the probability of rejecting the null hypothesis when it is actually true. So, changing the sample
size does not directly change the predetermined significance level. However, a larger sample size
can provide more precise estimates and reduce the margin of error, which can contribute to
stronger evidence for rejecting or accepting the null hypothesis. Furthermore, you mentioned that
a larger sample size allows for more accurate representation of the whole group. This is generally
true and I agree, as a larger sample size tends to provide more reliable results that can be
generalized to the larger population.
There are also ethical considerations to be considered. For
instance, researchers should ensure that their chosen significance level is appropriate to avoid
overly strict or lenient levels that may lead to incorrect conclusions. Additionally, when
determining sample size, researchers must consider ethical considerations such as minimizing the
number of participants exposed to potential risks.
Reply to Keith Epps
I agree that significance levels are indeed a crucial component of hypothesis testing, and it is
the researcher who chooses the significance level. In regard to your example, it seems not very
clear to me, however, I would like to add or clarify that the example provided about a dietary
supplement reducing the risk of a minor ailment seems to be focusing on the effect size or the
practical significance of the finding instead of the statistical significance. I would respectfully
like more clarification on this example. This is because, a reduction in risk from 2 out of 1000 to
1 out of 1000 might be considered a small change in practical terms, but it does not provide
information about the statistical significance of the result. However, that aside, I would like to
add that the level of significance, dictates the probability threshold at which the null hypothesis
is rejected. Sample size, can influence the statistical power of the test, which is the ability to
detect a true effect if it exists. A larger sample size generally increases the power of the test,
making it more likely to detect a significant result if one truly exists.
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