discussion board question and responses hypothesis testing

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Please provide an answer to the following discussion post and responses to my classmates:

(Answer this post) Describe a hypothesis test that you would like to conduct. Be sure to include the null and alternate hypotheses as well as the data you would need to collect to conduct the test. Discuss which level of significance you would use and why you would use that level. Further explain what you would do if you obtained a test statistic that was equal to the critical value.

(reply to these post)

I don’t know if everyone has had Subway or thought of this but every time order a sandwich I think to myself what size am I actually getting. One hypothesis test I would love to do would be if the subway footlong sandwich is actually 12 inches long like they advertise. My alternative hypothesis would be that it is not 12 inches but that is less and not living up the expectation. In theory, I would write that Subway advertises that they have a footlong sub sandwich. A footlong is equal to 12 inches. Meaning that every sub you get should be 12 inches. My alternative thinking would be that Subway footlong is not 12 inches but less. We would use the p-value approach to test against the null hypothesis.

To test this theory I would need to inspect several stores like at least 10 stores and buy at least one footlong sandwich from each store. I would use a standard measuring ruler and measure each sandwich. If the sandwiches are less than 12inches long than my null hypothesis would be not accepted and my alternate hypothesis is correct. In an article, I found online “Subway’s justification is that each footlong loaf is formed from exactly the same weight of dough but the inconsistencies of kneading, rising, shaping and proofing entail that on occasion some loaves fail to measure up”(Arumugam 2013). There are a lot of variables that we would need to take into value. This would be one-tailed test and all the alpha probability is placed in just one tail (Alexander, Illowsky & Dean).

I am very fond of Subway and will always eat fresh with them, but I will always know that the footlong is not always 12 inches because of the rising of the yeast and shape, etc is the main reason that it is not actual 12 inches. I don’t think that my null hypothesis would be true due to the fact that no bread baked is the same size as the other.

Reference:

Alexander, H., Illowsky, B., & Dean, S. (2017). Introductory Business Statistics. Openstax. Retrieved February 27, 2020 from: https://openstax.org/details/books/introductory-bu…

Arumugam, N. “Why Lawsuits Over Subway’s Short Footlong Sandwiches Are Baloney.” Forbes, Forbes Magazine, 28 Jan. 2013, www.forbes.com/sites/nadiaarumugam/2013/01/27/why-lawsuits-over-subways-short-footlong-sandwiches-are-baloney/.

(reply to this post)

Innovation is a huge buzz word in the military, finding ways to increase efficiency and do more with less is driving a constant search for improvement. More often that not, those fixes seem to take longer, and utilize more resources to get less accomplished. Recently, a new system was brough into the military for testing, that is designed to help load munitions on aircraft faster. The hypotheses is, that the average time that it takes a traditional crew to load an aircraft will be faster than the new machinery. According to Alexander, Illowsky, and Dean, the testing of a hypotheses requires that the opposite point of view must also be considered and tested as well as the possibility that there is not a difference between the variables, this is known as the alternative hypothesis, and null hypothesis respectively (2017). For this instance, the null hypothesis would be that there is no time difference between the traditional load crew, and the new machinery. The alternative hypothesis would state the new machinery is faster than the traditional crew.

To test this theory, a series of time trials would need to be conducted to collect adequate data. However, there are numerous variables that can go into loading an air craft, such as type of air craft, or the environment the aircraft is in, as well as variation between different load crews. To collect accurate data multiple samples, from multiple populations would need to be taken to ensure that the true average is represented. Further, to help ensure that the analysis is accurate a high significance level would need to be utilized. As Ogee, and Ellis put it, a low significance level of .05 translates into only a 5% chance that a conclusion is reached in which there is a difference, where none actually exists (2015). The .05 significance level mentioned above is a very common significance level and traditionally accepted. Further this significance level also defines the critical area, which defines the boundaries that if results fall within, they are abnormal enough to force the rejection of the null Hypothesis.

References

Alexander, H., Illowsky, B., & Dean, S. (2017). Introductory Business Statistics. Openstax. Retrieved from https://openstax.org/details/books/introductory-bu…

Ogee, A., and Ellis, M. (2015). Understanding Hypothesis Tests: Significance Levels (Alpha) and P Values in Statistics Retrieved from https://blog.minitab.com/blog/adventures-in-statis…

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