# M7-DRQ-PSY260

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Remember to respond to two peers while being respectful of and sensitive to their viewpoints. Consider advancing the discussion in the following ways:
· Post an article, video, or visual to reinforce a peer’s idea or challenge them to see their point from a different perspective.
· Engage in conversation with your peers around the topic of statistics in everyday life. Consider asking a question or sharing your own personal experience.
To complete this assignment, review the
. You will also need:
·
Norms of Practice for Online Discussion
·
Ethical Usage Practices
PEER 1-RW
Hello Class.
In the Ted Talk video (Donnelly 2005), he gives us examples of jury decisions and medical tests related to making false positive and false negative errors.His video connects to what I havelearned in this curriculum surrounding statistical decision making by demonstrating how easy itcan be to make Type I or II errors.Donnelly cited a hypothetical example of a false positive ortype 1 error for medicine.He illustrated that if a person were picked at random to test for HIVand they have a positive result, we might reject the null hypothesis that the individual does nothave the disease and make a type 1 error.Donnelly cited a hypothetical example of a false positive or type 1 error for medicine.He illustrated that if a person were picked at random to test for HIVand they have a positive result, we might reject the null hypothesis that the individual does nothave the disease and make a type 1 error.One consequence of making this Type 1 error mightbe that the individual suffers unnecessary stress by believing that they have HIV when theyactually do not.
In our daily lives, many students in our class may end up in statistical research, while others might be applying statistical concepts to the business world.In each case, having an awarenessand understanding of Type I and II errors is an important learning from our course.It is mybelief that making a Type I or Type II error is often equally problematic, but the specificconsequences of these errors will vary based on the matter in question. I would not argue thateither error in and of itself, is better or worse than the other.
In his blog, Steve Mathieu shares an interesting example about Type I and II errors. He takes us back to the fable of Aesop and “The boy who cried Wolf”.Mathieu makes the example that aType I error or false positive occurs early on in this story.When null hypothesis is that there isno wolf and the villagers incorrectly reject the null hypothesis during the early incidences inwhich the child is pretending that there is a wolf, a Type I error is made by the villagers.
I continue to hold the opinion that having an understanding of statistics is important for the general population. I still believe that while it is more important than in decades past to hold at least a rudimentary understanding of statistics, the general public is not interested in having or exercising this knowledge. It could be argued that SNHU’s programmatic theme of social justice can be applied if we each approach our future personal and work lives with the desire to be aware of statistics and statistical literacy in our daily lives.
I hope every one has a good rest of the week.
PEER2-DM
Question 1 & 2:
In the Ted Talk, there are examples as to how medical tests and jury decisions relate to false positive and false negative errors. This video showed me how easy it is to make type I and type II errors, and they are much more common than we sometimes realize. This video talks about examples of HIV tests and how a random person selected may have a positive result, we might reject the null hypothesis that the person doesn’t have the disease and thus making a type I error. A consequence of making the type I error is the person now thinking they are infected with HIV, when they actually aren’t. This can cause a lot of stress, panic, worry, and even cause them to handle their life differently. Our whole world is wrapped in statistics. The programmatic themes that tie in with this example are ethics, because it is unethical to diagnose someone with something they do not have and make them worry for no reason.
Question 3 & 4:
I believe that type I error is worse because a false positive can be stressful for almost any situation. A false positive can be devastating for someone trying to have a baby, and they receive a false positive pregnancy test. Or someone who is testing for an STD and they receive a false positive then overwhelm themselves with that. There are so many situations where I believe a false positive is worse, so type I error. I do believe the context in which the statistical decision is being made affects which error is worse. Like I said, a false positive pregnancy test for someone trying to have a baby definitely makes a type I error worse. Whereas someone who may be wrongly convicted, a false negative, would make type II error worse.
Question 5:
I do hold the same view that understanding statistics are essential in being an effective citizen. It is so important to know the type of data you’re looking at, what you’re reading, understanding how to interpret it, and to know what to do after you understand the data. Without knowledge of how to interpret these statistics, type I and type II errors are way more common.
Donnelly, P. (2005).How juries are fooled by statistics. Peter Donnelly: How juries are fooled by statistics | TED Talk. Retrieved June 14, 2022, from

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