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Introduction The two problems addressed signify critique on particular cases in which misuse of statistics is involved. One problem requires analytical evaluation of statement derived from a magazine advertisement while the second problem deals with justifying a reason a survey question can generate evaluation outcomes filled with errors. On each exercise, the type of statistical misrepresentation is identified, detailing how either scenario may not be a reliable source of info or formal query for research purposes.
Comment on this statement taken from a magazine advertisement: “In a recent clinical study, Brand ABC* was proved to be 1950 percent better than creatine!” Actual brand will not be named (Sobecki et al., p. 810).Type of Misrepresentation: Suspect SamplesComment: For one, the statement is missing numerical figures essential a reader’s understanding such as the probability that the new substance promoted would take effect within a specific confidence interval. Despite claiming that the product is 1950% proven effective, no actual proof is presented so the ad’s exaggeration could either raise suspicion or stir curiosity on potential consumers.
Readers may also find themselves trying to make vague sense of how recent the study was made since the claim does not go any further than mentioning ‘recent’ which could mean dating to a couple of years back. Moreover, the term ‘clinical’ appears insignificant unless replaced by a name of a credible health institution known to have conducted similar studies in the past. By not divulging the brand name or label, the advertisement runs the risk of making some of the readers think that it is a possible hocus-pocus or that without sufficient details, it emerges a detractor of another leading brand in the market.
Explain why the survey question “Do you think that it is not important to give extra tutoring to students who are not failing?” might lead to an erroneous conclusion (812).Type of Misrepresentation: Asking Biased QuestionsExplanation: The double negatives and the manner in which the question is made seems misleading as it occurs more disposed to convince someone to agree that tutoring students who pass is still important. Chances are, on one hand, the person being asked may be readily and psychologically conditioned to consider the importance of tutorial in any case without paying due regard on situations it is most needed, and on the other, he or she may find that passing students make no significant difference from the failing ones.
So the ambiguity of meanings attached to the question might cause results out of an erroneous understanding that tutorial is actually a necessity and the query sounds as if no second thoughts or further analysis is required. Conclusion It is quite obvious how the application of suspect samples in the first problem is demonstrated through an ad statement. Likewise, the second exercise consists of a biased question that directs response to a one-sided position. These examples altogether exhibit misuse of statistical figures or claims which happen in real life and are often inevitable especially in a capitalist society where they serve as schemes to improve monetary gain in sales and profit.
ReferenceSobecki, Dave et al. (2010). Math in Our World. 2nd ed. McGraw-Hill Science/Engineering/Math.
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