Manipulating Surveys

Authors, advertisers, and politicians rely on numbers for one important reason: people tend to believe them. They use surveys, polls, and other statistics to make their arguments sound more credible and more important. The problem is, it is just as easy to mislead with numbers as it is with words. Below are some examples of how numbers are manipulated and why they should not always be trusted.

In order to be able to reach accurate conclusions, numbers must be gathered correctly. There are two ways to do that:

1. Use an appropriate sample population. In a survey, you use a small number of people and apply the results to a large number of people. To make it accurate, a survey population should be:

■ large enough—if the sample number is too low, it will not be representative of a larger population

■ similar to the target population—if the target population includes ages 10-60, your sample can't be taken just from a junior high school

■ random—asking union members about labor laws is not random; asking one hundred people whose phone numbers were picked by a computer is

For example, if you survey people eating breakfast in a coffee shop about how often they eat breakfast outside the home, you will probably get a high number. Your sample population consisted only of people who were having breakfast out, and not any of the large number of people who never eat breakfast outside the home.

2. Remain un-biased. That means asking objective questions and creating a non-threatening, non-influencing atmosphere. Compare, "do you think people should be allowed to own dangerous firearms if they have innocent young children at home?" to "do you think people should be allowed to exercise their second amendment right to own a firearm?" In addition, if the person asking either of those questions is wearing a button that says "Gun Control Now!" or is holding up a loaded pistol, the environment is biased, and will influence the answers received.

Compare "we think you'll like Smilebright toothpaste better than Brightsmile," to "80% of respondents in a recent survey liked Smile-bright better than Brightsmile." The high percentage in the latter example is meant to tell the reader that most people prefer Smilebright, and you probably will, too. But how was that percentage figured? The survey consisted of asking five people who already declared a preference for gel-type toothpaste whether they liked Smilebright or Brightsmile. Therefore, there was no random sampling. Everyone in the group had the same preference, which is probably not true for a larger population.

Friendly Persuasion

Friendly Persuasion

To do this successfully you need to build a clear path of action by using tools if necessary. These tools would be facts, evidence and stories which you know they can relate to. Plus you always want to have their best interests at heart, in other words, you know what is good for them

Get My Free Ebook

Post a comment