Statistics to Mislead Statistics Can Be Misleading.

¶ … Statistics to Mislead Statistics can be misleading. People can use misleading statistics to persuade others to buy a product or share their point-of-view. Britain's Sunday Times, for example, alerted readers more than a decade ago to this tactic, showing that insurance companies often use misleading figures to scare consumers into buying expensive coverage they may never need (Cooper, 2001). In Mathematics in Our World, Bluman (2011) provides numerous examples of the ways statistics are presented to lead the reader to a false conclusion.

This paper answers two of the questions in Bluman's textbook about misleading statistics. No mathematical calculations were required in answering these questions. One need only to give some thought to the information presented. Statistics, when read quickly and without consideration, may appear to tell a certain story, often one that is meant to alarm the reader and/or incite action. Closer examination, however, can reveal a completely different story. The math problems are as follows: 4.

In many ads for weight loss products, under the product claims and in small print, the following statement is made: "These results are not typical." What does this say about the product being advertised? (Bluman, 2011, p. 810) To sell its weight loss product, a company needs to show that it can yield dramatic results. People who buy these products are often frustrated and desperate because other methods of weight loss have failed. The company will show a result from the top of the range to entice buyers.

An average or mean would be a lower number, which may not attract as much attention in advertising. The advertising shows what is possible, not what someone can necessarily hope to achieve. When results are not typical, it may also mean that the individual augmented the weight loss program in some way. For example, celebrities who endorse weight loss plans that deliver home meals may have also hired personal trainers and outfitted a home gym with expensive equipment, neither of which is within reach of the average dieter.

People may pay for weight loss products but fail to use them or use them incorrectly. This is why, as with gym memberships, payment in advance is required rather than "pay as you go." Many people start a weight loss plan with enthusiasm but do not follow through. That is typical behavior and not the behavior model that sells products. Weight loss ads tell the reader (or viewer) nothing about the population that used the product.

We do not know how many people used the product, the duration of use, age range of users, or anything about the users' health histories. For example, forty-nine people could have used the product, each losing only a few pounds. The fiftieth person could be the one to lose a significant amount of weight, perhaps by augmenting the diet product. We just do not have enough information to make an intelligent decision about the efficacy of the product. 22.

For a specific year, there were 6067 male fatalities in the workplace and 521 female deaths. A government official made this statement: "Over 90% of the fatal injuries the past year were men, although men accounted for only 54% of the nation's employment." Can we conclude that women are more careful on the job? (Bluman, 2011, p. 812). One cannot conclude from this data that women are more careful on the job. There would need to be direct comparisons according to the type of job and the workplace setting where the fatalities take place.

In general, many more men than women are in potentially dangerous jobs: coal miner, lumberjack, deep sea fisherman, power company lineman, infantry soldier, and others. Fatality rates in these jobs are higher than other jobs. The fatality rates are a factor of the job, not the gender of the person engaged in the work. Although women are increasingly seen in jobs that were once considered the exclusive domain of males, there are still a disproportionate number of women in jobs such as teacher, nurse and administrative assistant.

There is nothing inherently dangerous in these jobs. In 2011, Forbes Magazine reported the national rate of occupational fatalities is 3.3 deaths per 100,000 workers. As pointed out, many deaths were unrelated to the work itself. Four in ten workplace deaths in 2009 took place while driving. In addition, 18% involved assaults and homicide (Whelan, 2011). Forbes also reported other leading causes of death in the workplace were attributed to explosions (3%), falls (14%), exposure to harmful substances (9%) and being struck by objects (10%).

Again, industries that see these kinds of accidents include construction, transportation and warehousing, fields that typically have a disproportionately high number of male workers. Forbes also noted that government statisticians only track safety for large job categories, where there are at least fifteen fatalities out of 20,000 full-time employees (Whelan). Statistics therefore do not provide a complete picture of the American workforce. Not everyone understands how statistics are used and misused.

For example, one cancer drug claims to reduce one's risk of cancer by 50%, while another eliminates cancer in one out of 100 people. Surprisingly, these numbers refer to the same drug, the first statistic using relative risk, the second using absolute risk. In a trial involving one hundred people, two would normally get cancer during the duration of the trial, but when all one.