Correlation Studies

The gathering of information is not the only time during which manipulation can occur. Once numbers are obtained, they must be interpreted or evaluated. This step also has plenty of opportunities to distort the truth. As an example, let's look at comparisons between two sets of information between which there may be a connection. These types of comparisons are commonly referred to as correlation studies.

Researchers use correlation studies when they want to know if there is a link between two sets of data. For example, some questions that might be answered with a correlation study are:

■ Is there a connection between full moons and an increase in birth rates?

Margin of Error

Most survey results end with a statement such as "there is a margin of error of three percentage points." What does this mean? It is a statement of how confident the surveyors are that their results are correct. The lower the percentage, the greater their confidence. A 3% margin of error means that the sample population of the survey could be different from the general population by 3% in either direction. Let's say a survey concluded that "55% of Americans want to vote for members of the Supreme Court." If there is a 3% margin of error, the results could be either 58%, or 52%, or anywhere in between, if you conducted the identical survey asking another group of people.

As an example of the importance of knowing the margin of error, imagine the results of a political poll. The headline reads, "President's lead slips to 58%; Republican front runner gaining momentum, 37%." The following article notes that last week, the results were 61% for the president, and 34% for the Republican candidate. There is a margin of error of 4%. That means that there is really no difference between the two polls. No one is "slipping" or "gaining momentum." The margin of error in this case tells the real story, and the news article is wrong.

■ Does having a high IQ indicate that you will have a high income level?

If research at five area hospitals shows that during a full moon, 4% more babies are born on average than on nights in which there is no full moon, you could say there is a small but positive correlation between the two sets of data. In other words, there appears to be a connection between full moons and birth rates.

However, many studies have shown that any perceived correlation is due in fact to chance. There is no evidence to support the theory that the phases of the moon affect human behavior in any way. So, even when there is a positive correlation, it does not necessarily mean there is a cause and effect relationship between the two elements in the correlation study.

For the second question, if a study showed that Americans with the top 5% of IQ scores made an average of $22,000 a year, while those in the middle 5% made an average of $40,000, you would say there is a negative correlation between IQ and income levels. To describe the results of the study, you could say that there is no evidence that IQ determines income level. In other words, you do not need to have a high IQ to make a lot of money.

This conclusion is obvious. But let's look at how these same correlation study results can be used to come up with a ridiculous conclusion. The second example shows that there is no connection between a high IQ and a high income level. Is that the same as saying that "the dumber you are, the more money you will make?" Of course it isn't. This type of conclusion shows one of the dangers of correlation studies. Even if the study uses accurate data, the way in which it is interpreted can be wrong, and even foolish. When you encounter a correlation study, as with survey and poll results, do not assume the numbers and conclusion are correct. Ask questions, and look at supporting data. Does the study make sense? Or does it seem too convenient for the advertiser/politician/new reporter/ author who is using it? Think critically, and do not rely on anyone's numbers until you determine they are true and valid.

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

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