I recently completed a math test and as I was making my way through the sixty plus problems which appeared on the screen, I chanced to encounter one of the questions which requested information on the word “median”. This made me recall a previous course in statistics, which I had taken several years ago. I can recall how I really hated that course and could not for the life of me understand why anyone would have to use the principles explained in it. It took a while before the rationale for learning statistics sink in. I present this rant to those students who are required by their schools to complete a course in statistical arguments. Hopefully it helps explain why we use this strange math method at all.
During this rant, I would like to reiterate a few notes on several tools which are useful in creating and eventually analyzing various bits of data. We are all familiar with the term average and the simple process which is used to figure these data elements. The problem is that not all interpretations of the word average have similar meanings and as a result confusion usually reveals its ugly head. To remedy this misunderstanding, we have three effective words which we can use to convey a similar but more concise meaning. They are mean, median, and mode. The key to understanding these concepts lies in how we employ these measurements in our daily use. We are often shown various formulas and procedures necessary to complete the calculations to their correct conclusions along with directions on how to compare the three measurements properly but at this time let’s just skim the surface.
Let’s for a moment cover the distribution characteristics of any available data. These data traits included modes which involve the variants of symmetry and skewed variations. This data integrated into our conclusions is identified as smooth curves in place of the actual data sets usually employed. These qualities approximate the true distribution. We can also at this time review our veritable understanding about the right and left skewed data which revealed specific graphic styles relating to the data in question. That segment of our discussion would likely conclude with instructions in the measurement of variations. Finally, it would behoove us to become versed in how to calculate the standard deviations of any data set using the standard deviation formula.
If we are actively involved in the principles of statistics often open up various opportunities towards taking advantage of the information and principles which are present in any study of data. In this context, we are afforded several excellent examples of such use. A perfect example of this would be determining the mean SAT scores from a specific sampling of students and then comparing our own personal score with the mean to see exactly where we would stand. The same process could be applied to the GRE scores as well, since specialized scores are required by certain graduate schools for admission. The use of our statistical information would also be useful to predict school test scores based upon the national standardized tests. These results would provide us with a mean score along with standard deviations from which we can then judge our performance on the tests.
Finally, we can attain justification for our statistical knowledge in a host of other ways. If your job involves retail sales as mine occasionally does (I sell survival CDs part time) than the principles being taught could tell me what CDs are the most popular in my complete line of selections. To accomplish this I would begin by maintaining records on which CDs are sold daily for one complete month. Next, I would draft up a graph such as a bar graph to see which ones I have sold the most of.
You won’t become a math whiz by reading this article and it really wasn’t the intent that I had in mind. I just thought that you might perhaps gain some new insight and understanding as to why we study the statistics.
