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Data-Wiseness per Joel Best

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Data-Wiseness per Joel Best All Sections No unread replies.No replies. This is the first of three Discussion Forums involving Data-Wiseness and Data-Driven Decision Making. This Forum will focus on the Stat-Spotting text by Joel Best. The book is rich with sound statistical critical thinking as well as helpful advice. For this week, please do make at least one main post and one response post to another student's main post. Try to keep your posts directed to substantive content expressed with reasonable brevity (200 - 300 words maximum if possible). You may choose from the following prompts or initiate your own topic areas related to this Stat-Spotting text: 1. In section B, several benchmark numbers are noted. In your field(s) of interest, do you have any particular benchmarks that help you deal with various claims that may seem dubious to you? 2. Section C deals with Blunders (the "underage drinkers" example on p. 25 is illustrative). Have you observed a similar blunder(s)? What was it, was it resolved, and how was it resolved? 3. Have you ever observed Expanding Definitions as demonstrated in the Overnight Increase in Overweight Americans example starting on p. 44? If so, describe the definition change and address it's explanation if known. 4. Related to #3 above, note the Bloated Figures example starting on p. 61 in Section F on Measurements. Have you observed conflicting reports from the same institution or agency? If so, what was the conflict, and how might it have been resolved (or not)? 5. Three examples in Section G, Packaging, G8 - G10 may be of interest to you, particularly Correlations and Discoveries. Note that the Discoveries example involving medical research launches from the work of John Ioannidis who is the subject of one of the articles in Module 1 Bundle 2. Please feel free to address any of these articles in a brief evaluation.
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Data-Wiseness per Joel Best Student Name College/University Course Professor Name Due Date Section C deals with Blunders (the "underage drinkers" example on p. 25 is illustrative). Have you observed a similar blunder(s)? What was it, was it resolved, and how was it resolved? I encountered a similar situation to Best's (2013) statistical analysis on “underage drinkers.” I was on the planning committee for launching a new product made available by a manufacturing company to target an identified market niche. In this case, the financial forecasting values of this manufacturing company were more than double what was realistically achievable. During the review process, we found that some crucial demand and pricing strategies were not considered. Best (2013) reports that many statistics result from strings of calculations where numbers from different sources are manipulated to obtain a desired outcome. The manuf...
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