As we\u2019ve seen, flaw questions on the GMAT follow predictable patterns: the flaw always in some way addresses either how the evidence is being interpreted to lead to the conclusion, or how the evidence was obtained. Let\u2019s take a look at a few specific examples of common GMAT flaws.
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\nAt Company X, 15% of the male executives took advantage of the corporate \u201cFamily Leave\u201d program last year, enjoying 6 weeks of paid sabbatical after a birth or adoption in their family. Only 10% of female executives at Company X took advantage of the program. Therefore, it appears that more male executives than female executives at Company X are interested in programs that promote leave options for personal reasons.<\/p>\n<\/div><\/div>
\nThere are actually two major flaws here, and we\u2019ll look at the one that ISN\u2019T the title of this sub-section first, just to get it out of the way: the evidence isn\u2019t sufficient to support the conclusion. The conclusion is about the \u201cinterest\u201d of executives in \u201cprograms that promote leave options for personal reasons,\u201d but the evidence only discusses percentages of executives who were involved in one specific program.\u00a0 Drawing a conclusion about programs in general based on that evidence is unsound. Also, participation alone is not necessarily indicative of the interest in the programs; maybe people ARE interested, but just haven\u2019t had new babies in their families.
\nThe more standard flaw here, though, is the \u201creal numbers versus percentages\u201d issue. Evidence is presented about percentages, and based on that evidence, a conclusion is drawn about quantity. But the conclusion is flawed: what if there are 100 male executives at Company X, and 200 female executives? In that case, there would be 15 male executives taking Family Leave, and 20 female executives; since 20 is clearly more than 15, the conclusion would not be properly drawn in that case.\u00a0 We can see, then, that percentage evidence alone is not sufficient to support a conclusion regarding \u201creal number\u201d quantities.
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\nStudies focusing on North Americans show that single men have an average lifespan of 72.1 years; married men have an average lifespan of 73.4 years. However, married women live an average of 75.4 years, 2.1 years less than single women, who have an average lifespan of 77.5 years. Researchers have concluded, based on the data from those studies, that husbands suck the life-force out of their wives, prolonging their own lives at the cost of their spouses\u2019 longevity.<\/p>\n<\/div><\/div>
\nThe issue here is that there is a correlation between two occurrences (the increased lifespans of married men and the decreased lifespans of married women) and the argument inappropriately assumes that there must be a causal link between those occurrences. Whenever you see an argument that presents two events\u2014let\u2019s call them X and Y– that occur together, and that then concludes that one event, X, must be causing the other event, Y, you should look for the possibility that Y in fact causes X, or that some outside factor, Z, is causing both X and Y.
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\nIn order to successfully navigate the Great Lakes Trail, a 47-mile hiking trail fraught with unsteady terrain, one must have a pair of supportive hiking boots. Drew recently purchased a pair of the most comfortable and supportive hiking boots on the market. Therefore, Drew should have no trouble navigating the Great Lakes Trail when he goes on his hiking trip next month.<\/p>\n<\/div><\/div>
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\nNow, I know we\u2019ve seen a lot of necessary\/sufficient issues in past discussions, but in flaw questions, the application is simpler. The correctly-identified flaw here would be that the argument takes a condition that is necessary for achieving the goal of completing the hike, and has treated it as though it is sufficient. Good boots are necessary; without them, Drew couldn\u2019t make the hike. But are they ENOUGH? What if Drew has a horrible virus and can\u2019t even get out of bed, let alone go for a 47-mile hike? The boots are not, by themselves, SUFFICIENT to ensure success on the hike. As a reader, be on the lookout for arguments that don\u2019t differentiate between necessary and sufficient conditions.<\/p>\n","protected":false},"excerpt":{"rendered":"
As we\u2019ve seen, flaw questions on the GMAT follow predictable patterns: the flaw always in some way addresses either how the evidence is being interpreted to lead to the conclusion, or how the evidence was obtained. Let\u2019s take a look at a few specific examples of common GMAT flaws. There are actually two major […]<\/p>\n","protected":false},"author":1,"featured_media":28890,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[55],"tags":[56,516,84],"_links":{"self":[{"href":"https:\/\/wpapp.kaptest.com\/study\/wp-json\/wp\/v2\/posts\/13450"}],"collection":[{"href":"https:\/\/wpapp.kaptest.com\/study\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/wpapp.kaptest.com\/study\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/wpapp.kaptest.com\/study\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/wpapp.kaptest.com\/study\/wp-json\/wp\/v2\/comments?post=13450"}],"version-history":[{"count":2,"href":"https:\/\/wpapp.kaptest.com\/study\/wp-json\/wp\/v2\/posts\/13450\/revisions"}],"predecessor-version":[{"id":36048,"href":"https:\/\/wpapp.kaptest.com\/study\/wp-json\/wp\/v2\/posts\/13450\/revisions\/36048"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/wpapp.kaptest.com\/study\/wp-json\/wp\/v2\/media\/28890"}],"wp:attachment":[{"href":"https:\/\/wpapp.kaptest.com\/study\/wp-json\/wp\/v2\/media?parent=13450"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/wpapp.kaptest.com\/study\/wp-json\/wp\/v2\/categories?post=13450"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/wpapp.kaptest.com\/study\/wp-json\/wp\/v2\/tags?post=13450"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}