Prelude to Statistical Data Analysis:

¶ … Prelude to Statistical Data Analysis: Raw Data's Wardrobe in the Form of Bar Graphs, Pie Charts, Line Graphs, Stem and Leaf Displays, Box and Whisper Plots.

Regardless of the type of chart or graph you use to illuminate or express a concept or idea they all have one thing in common; namely, to communicate, via picture, what is being studied or what is happening. To this end the research investigator, regardless of discipline, wanting to show what is taking place make use of bar graphs, pie charts, line graphs, leaf displays and Box and Whisper Plots. Unfortunately, however, those who are not well grounded and informed about statistical processes oftentimes rely on these pictorial presentations to draw conclusions or make inferences about what is being studied and evaluated. When this happens in the research arena, wrongful decisions are oftentimes made about important matters. Nonetheless, graphs and charts are an important step in achieving what statistical processes will eventually resolve. The remainder of this report will focus on one form of pictorially presented data, namely, the pie chart, wherein purpose and example will be discussed.

Like bar graphs pie charts, or circle graphs, are a pictorial means whereby the individual can present information in a simple non-statistical form. Further, like bar graphs, pie charts are usually employed to compare percentages of the same whole. Unlike bar graphs, they do not use a set of axes to plot information or data points. Pie charts display percentages and are used to compare different parts of the same whole. With pie charts, it is important to remember how they are sometimes misrepresented in research situations, namely leaving out parts of the whole and not defining what the whole really is. When a part of the whole is omitted the percentage values of the remaining parts that are displayed are increased. When the whole is not well defined, the reader is unclear what the parts represent. Again, a pie is a graphical representation of how many individual parts contributed to the total.

Take for example a human resource manager who is interested in how three different departments in a business situation waste time on the internet on a given day when they should be doing company business. The human resource person would collect data through a time study process and determine the number of times each employee in each department logs on and off the internet for personal business. The times would be collected, added together and the times of each department converted to percentages. In the example presented, the human resource manager can report that, cumulatively, the employees in Department 1 spent a total of 5 hours a day on the Internet, Department 2 employees 2 hours a day and Department 3 spent 6 hours. The raw numeric count is then converted to percentages and the pie chart would look like the following (Ohlson, 2005):

The solution to the data presented above is calculated as follows:

The total (sum) of 5 and 2 and 6 occurrences is 13

http://www.algebra.com/cgi-bin/plot-formula.mpl?expression=5%2F%285%2B2%2B6%29&x=0001