# Chapter 2: Deceptively Mean

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When providing statistical data and information more often than not a researcher uses the average to give quality to the research they have accumulated thus far. However depending on how these averages are used and determined the data can easily become a deceptive ploy to give a perception of an illusion to the reader or partaker of this statistical information. There are three different types of averages which are, mean, median, and mode. Though each of these types is legitimate in their own right each plays a different factor within the summarization of the data. However due to the loose meaning of the word average very often the differences in each of these types of averages are taken advantage of in order to persuade the audience of those providing the data in attempt to create or trigger a particular response.

Using each type of average in an appropriate manner can be easily done however it is important that you are knowledgeable in the differences between the three first. The mean average takes the sum total of all the collected data and then dividing that total by the amount of participants within the study. This type of average can be used when figuring out things such as the average grade on a quiz for students within a math class. The next type of average is referred to as the median average. The median average is determined by taking an overall set of values or data and finding out which falls directly in the middle. The final type of average is called the mode average. This average accounts for the most often occurring item within a data set. This type of average help to show how frequent a particular portion of the data is common across the group of subjects being studied. In becoming knowledgeable about each type of average that can be used it is very important that those displaying statistical data are ethically using the information to inform their audience and not to just influence the audience’s perception with deception.

The mean can be used to decieve an audience when outliers are not taken into account as well. Example1 Within this example a real estate agent takes the  income values of individuals within the communtiy and averages them for the overall neighboorhood to represent those who work at home within the communtity. However the survey does not specify who all is included within the breakdown of the study. This can become an issue of deception if a stay at home mom reports her income of her household and her husband is a CEO at a multi-million dollar corporation. Especially if the mom two doors down household income is only hitting 50,000 dollars.  This type of mean distracts from the true intended purpose of the survey. Another example of this can be found in Example 2.

Within Example 3 it is shown how organizations can use the better fitting mean to represent data if it gives them a better appearance. By determining which mean shows their employees at an higher pay rate than other oraginzations the company within this example has the ability to attact more potential employees to their oragnization while also appearing to being more resourceful than other organizations. These examples showcase why it is very important to look close into the reserach we do as consumers within this deceptive market because we otherwise can't be to sure as to what is truly being said by the numbers.