Brian Galvin is the Director of Academic Programs at Veritas Prep, where he oversees all of the company’s GMAT preparation courses.
We live in a quantitative society, which is a major reason that your GMAT score is so important – we like to base our decisions on numbers. When someone tells you, however, that they “ran the numbers”, is that explanation sufficient for acting on their research? Every day we’re bombarded by numbers that seem to support decisive action on our part – “save up to $50/month”; “95% fat free” – but those statistics, correct as they may be, may not actually mean that their purveyor’s conclusion – “buy this product” – is the best one for us. To save up to $50/month, we’ll likely have to spend much more than that on nonessential purchases; that 95% fat free statistic is a clever way of saying that the product is 5% fat, and the potential exists that your body will convert much of the other 95% to fat pretty quickly, anyway.
Simply put by America’s favorite simpleton, Homer Simpson, “you can use facts to prove anything that’s even remotely true.”
As a post-MBA manager, you’ll need to make quite a few decisions each day, often with lobbyists on at least one side supplying statistics that may resemble the figures above in their tangential logic. Accordingly, one of your major responsibilities will be to determine whether the case that someone pressing you for a decision makes is actually relevant to the decision.
The GMAT tests that quite often on its Critical Reasoning section, offering up statistical evidence that doesn’t quite lead to the stated conclusion, and asking you to submit an answer based on that mistake, For that reason, whenever you see statistics used on Critical Reasoning problems, be sure to look for a gap in logic between the statistics and the conclusion. Consider the following question, which appears courtesy of the Graduate Management Admissions Council (GMAC):
During the Second World War, about 375,000 civilians died in the United States and about 408,000 members of the United States armed forces died overseas. On the basis of those figures, it can be concluded that it was not much more dangerous to be overseas in the armed forces during the Second World War than it was to stay at home as a civilian.
Which of the following would reveal most clearly the absurdity of the conclusion drawn above?
(A) Counting deaths among members of the armed forces who served in the United States in addition to deaths among members of the armed forces serving overseas
(B) Expressing the difference between the numbers of deaths among civilians and members of the armed forces as a percentage of the total number of deaths
(C) Separating deaths caused by accidents during service in the armed forces from deaths caused by combat injuries
(D) Comparing death rates per thousand members of each group rather than comparing total numbers of deaths
(E) Comparing deaths caused by accidents in the United States to deaths caused by combat in the armed forces
The conclusion itself – it was no more dangerous to be serving in the military than to be at home – should seem dubious, and the statistics used, though true, don’t directly support that logic. Why? In a nation of 200 million or so at the time, the vast majority of citizens did not serve in the military. There were simply far more people staying at home as civilians than there were soldiers serving in the war effort, so the 375,000 homeland deaths represent a much, much smaller percentage of the population than do the 408,000 military deaths. The problem in the statistics is one of sample size, and the statistics don’t provide enough direct comparison of the two groups to be able to make the stated conclusion.
The study proposed in correct answer choice D, which would demonstrate the results on a percentage-of-population basis, would provide a better comparison, and reveal the absurdity of the conclusion. More importantly for your study of the GMAT (and for your role as a consumer), if you train yourself to be skeptical of statistics, you’ll avoid making bad decisions based on stats that don’t hit the mark.
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