2 Discussions word count on each is listed below!

#1 Examples of Hypothesis Testing in Research [WLOs: 1, 2] [CLOs: 1, 4, 5] (250-350 word discussion)

Locate an example of a research study that uses hypothesis testing. Explain whether the study describes its hypothesis testing procedure explicitly or implicitly, based on the explanations in the Methodology section. Finally, discuss what this statistical technique allowed the researchers to accomplish and/or conclude in the study.

#2 Hypothesis Testing [WLO: 1] [CLOs: 1, 4, 5] (300-400) word discussion!

Based on the quotes below, along with this week’s assigned readings and Instructor Guidance, discuss why hypothesis testing is important in research. Also, pick one quote in particular and analyze it’s meaning!

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https://www.goodreads.com/quotes/search?utf8=%E2%9C%93&q=statistics&commit=Search

There are strengths and weaknesses associated with the hypothesis testing procedure. For this discussion, begin by reviewing the concept of hypothesis testing in your textbook. Then, keeping this in mind, read the following quotes:

• “Your relevance as a data custodian is your ability to analyze and interpret it. If you can’t, your replacement is due.”—Wisdom Kwashie Mensah
• “Be careful of averages and how they’re applied. One way that they can fool you is if the average combines samples from disparate populations. This can lead to absurd observations such as: ‘On average, humans have one testicle.’”—Daniel J. Levitin, A Field Guide to Lies: Critical Thinking in the Information Age (2016)
• “How results that are not indicative of anything can be produced by pure chance—given a small enough number of cases—is something you can test for yourself at small Just start tossing a penny. How often will it come up heads? Half the time of course. Everyone knows that. Well, let’s check that and see…. I have just tried ten tosses and got heads eight times, which proves that pennies come up heads eighty percent of the time.”—Darrell Huff, How to Lie With Statistics (1954)
• “With enough mental gymnastics, just about any fact can become misshapen in favor to one’s confirmation bias.”—Criss Jami, Healology (2016)
• “A small sample, we repeat, is rarely the big scientific problem. Interpretation is.”—Stephen Thomas Ziliak, The Cult of Statistical Significance: How the Standard Error Costs Us Jobs, Justice, and Lives (2008)
• “We may at once admit that any inference from the particular to the general must be attended with some degree of uncertainty, but this is not the same as to admit that such inference cannot be absolutely rigorous, for the nature and degree of the uncertainty may itself be capable of rigorous expression.”—Sir Ronald Fisher
• “It is worth looking closer and remembering something Marcos Alvito told me: Statistics are like a bikini. They show so much, but they hide the most important parts.”—Dave Zirin, Brazil’s Dance With the Devil: The World Cup, the Olympics, and the Struggle for Democracy (2014).