Complete Business Statistics Discussion Post

Hypothesis TestingHypothesis testing typically begins with a theory, a claim, or an assertion about a particular parameter (mean or proportion) of a population.The Federal Trade Commission (FTC) is an independent agency of the U.S. federal government charged with preventing unfair or deceptive trade practices. It regulates advertising, marketing, and consumer credit practices, and also prevents antitrust agreements and other unfair practices.The FTC publishes press releases regularly about health and fitness claims athttps://www.ftc.gov/news-events/media-resources/truth-advertising/health-claimsHealth and Fitness Claims. Retrieved from https://www.ftc.gov/news-events/media-resources/truth-advertising/health-claimsFind a claim about a product or service from one of the press releases listed in the FTC website.Read through these and select one of interest to you that has not been picked by anyone else yet in class.Initial Response: Formulating the HypothesisSummarize the advertising claim as shared in the media. What population parameter is the claim about? (Hint: Focus on a population mean or proportion, such as the mean weight of a cereal box, or the proportion of fast-food orders filled correctly.)If you were to formulate a hypothesis test about this product/service, what would your null and alternative hypothesis be? (Be sure to use all the correct notations for Ho and Ha.)State whether you have a one-tailed or two-tailed test (Be sure you use the correct inequality signs).See Example post.First response: Review one of your classmates’ post. In the context of their hypothesis test, discuss what the Type I Error and Type II Error would mean using a Decision Table as your guide. What level of significance would you suggest based on what a Type I Error or Type II Error would mean?Recall that:Type I Error is defined as rejecting the null hypothesis when in fact it should be accepted. (i.e. “False Positive,” “False Alarm,” defendant found guilty when in fact innocent)Type II Error is defined as accepting the null hypothesis when in fact it should be rejected. (i.e. “False Negative,” defendant found not guilty when in fact guilty)
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Unit 5 Discussion Example – First Response to a Classmate’s Post
First Response: First response: Review one of your classmates’ post. In the context of their hypothesis test,
discuss what the Type I Error and Type II Error would mean using a Decision Table as your guide.
What level of significance would you suggest based on what a Type I Error or Type II Error would mean?
Recall that:
Type I Error is defined as rejecting the null hypothesis when in fact it should be accepted. (i.e.“False Positive”
, “False Alarm”, defendant found guilty when in fact innocent)
Type II Error is defined as accepting the null hypothesis when in fact it should be rejected. (i.e. “False
Negative”, defendant found not guilty when in fact guilty)
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On May 24, 2016: Mosquito Shield Bands (made by Viatek Consumer Products Group) is a bracelet that
contains mint oil and promises to protect people from mosquito bites for up to 120 hours. Viatek claims that
Mosquito Shield Bands create a “vapor” barrier that can shield anyone within five feet for 96 to 120 hours.
https://www.ftc.gov/news-events/press-releases/2016/05/marketers-mosquito-shield-bands-pay-300000barred-making
Null hypothesis, H0: µ = 96 hours
Alternate hypothesis, Ha: µ < 96 hours Type I Error: Our evidence is showing that the mean time is not 96 hours but in reality it was. Type II Error: Our evidence is showing that the mean was 96 hours, but it really wasn’t that long of protection! Decision Reject Null, P< alpha Cannot Reject Null, p >= alpha
Null is True
TYPE I Error : You wrongly
assume that the Shield Bands do
not protect you for 96 hours. So,
you also use other mosquito
protection methods. Not a big
deal!
Good decision
Null is False
Good decision
TYPE II Error : You wrongly
assume that the Shield Bands
protect you for 96 hours. You are
not as protected as you think and
you could be at risk of getting
bitten by a mosquito. Not a good
idea!
Based on the Type I error and it is not a big deal if we have this error, I would suggest a higher level of
significance since we want to be really sure that our customers are not getting a product that doesn’t do what
it says it should do! I would choose a = 0.01 (99% confidence level).

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