Increasing your intepretation of Research Findings, Dont ignore the Average

The Average can be your Best Friend

Whenever you are dealing with a mouth full of data there is always this thing of trying to understand what it really means. Imagine being a researcher who has to struggle with over a thousand entry's of data, how do you actually improve your understanding? When doing a data analysis, you can be sure that you are not alone in improving your understanding of research findings. However, it is disappointing sometimes that some researchers choose to ignore the use of a very fundamental approach in research and that is the finding of an average. Averages are indeed very important in the world of mathematics, physics, chemistry and even biology. You don't need to run to a very sophisticated methodology just to interpret very basic statistics. Simply find the average and play around with understanding what these figures mean. However it is first important that we understand what an average is and how it has helped researchers and others in this day and age. We will also understand the draw backs. Lets get started with the data analysis shall we.

Mean, Median and Mode; Different faces of the Average

Usually averages are defined as the mean and the mean as the average. So most people look at only one average which is the mean. The mean is widely used in science and it has really helped interpret research findings in a significant effective way. When you want to find the mean, you are not only looking for a numerical value but you simply want to come up with a single value for a set of values. Lets say you are doing a research on how much income people under the age of 30years earn. You are going to discover in your research that people earn a wide range of income from as high as $ 8000 to as low as $500. But in your data analysis and consequently reporting, you want people to have a general understanding of how much individuals earn because there are all these variations. Remember some may be earning $8000, while others may be earning $2000 or lower. In order to report one figure to the general audience, you have to report the average. Assuming you know this already, lets briefly define these different averages shall we.

1. Mean; Back to the example, you interview 5 different people who are earning 5 different incomes..how do you find the mean.
Individual A = $ 8000
Individual B = $ 5000
Individual C = $ 4500                                Mean= (8000+5000+4500+1000+500)/5 = $ 3800
Individual D = $ 1000
Individual E = $ 500

Answer: So on average people earn about $ 3800. However, in your research this may be a misleading statement at times because some people don't actually earn so high. You still have the Individuals D and E you see. But let not that bother you because as it is you are a researcher who must make sure that you emphasis in your report how much the lowest and the highest earn.

2. Median; The median is simply the middle value when the numbers are put in order. So lets put the various incomes in order shall we.

Incomes in order= $500 , $1000, $4500, $5000, $8000

What is the middle value here, you guessed well researcher it is $ 4500.

3. Mode; The number or set of number that occurs the most. Lets say you have a set of numbers 4, 5, 8, 20, 8, 76, 90, 5, 5, 8, 10 , 8. Which number occurs the most?? It is definitely 8. So 8 is your mode researcher.

Challenges of the Mean in Research

The mean definitely has a couple of challenges when you come to think of it especially when you as a researcher are doing your data analysis and want to make significant sense to it. Remember data analysis simply entails you bring out the information and you want to be smart too about it. One of the challenges with mean is that it doesn't really give a true picture. For example we saw that in the example above, on average people earn $ 3,800. But in reality no body even earns the figure $ 3,800. You have people earning as low as $500. In your Data analysis you will discover that the mean value can be tremendously affected by a slight change in the sample group, especially if it is small. Remember in the Income example our sample group only had 5 individuals, now lets say one of those individuals decided not to show up for the interview...How will the mean change. Lets say we remove individual A from the sample, in our data analysis our new mean will be $2750. So there has been a slight significant drop.

So as a Researcher or Data analyst you have to make sure that your sample group is large and its characteristics are representative of the general population. This was really an interesting article wast it guys but be sure to keep on reading more because next time we are going to look at research topics that only the real gurus like to here about.