Reviewing student assignments, I come to live with the fact of life that there is much to be desired in terms of creativity, critical thinking, depth, style, understanding of concepts, presentation, grammar and written language.
Looking back at the assignment which included the use and interpretation of graphs to visualise proportions, I suddenly thought I would make a post on graphs and how they can aid visualisation, and share with you the reader of this website-blog, and this post in particular.
In the course of your work as a HIM/MR professional, you must have prepared graphs using the computer. Chances are you prepared pie charts, the stacked bar(either vertical or horizontal bars), and just plain bar graphs and line graphs.
Since I had started posting on JCI Standards, I remember well when I used radar charts to display compliance ratings in medical records review findings report while working with my JCI experiences. I shall talk more on this in my coming post on the JCI Standard MCI.19.4.
A radar chart looks like this one:
Now, let us look at 8 ways to represent data we churn out each day, visually to represent proportions.
Pie charts and stacked bars are two ways used to represent proportions, you have used it!
You used a pie chart(WAY 1), which is a circle which represents the whole, and the size of each wedge represents a percentage of that whole, all wedges add up to 100 percent. For example, you may have presented the 10 leading causes of mortality in a pie chart for a particular year, and used the stacked bar chart (WAY 2) to represent for example proportions of 10 leading causes of morbidity for a number of years in a vertical stacked bar chart.
Likewise these other 6 graph types can also be used to represent proportions.
The donut (WAY 3) is the same idea as the pie, but with a hole cut out in the middle. Here is one example:
The stacked area chart(WAY 4) is used to show changes over time for several variables. You can use it for percentages, where the vertical always adds up to 100 percent, or you can use raw counts if you’re more interested in the peaks and valleys. Here is an example:
The treemap(WAY 5) uses the areas of rectangles to show relative proportions. It works especially well if your data has a hierarchical structure with parent nodes, children, etc. One example is :
A Voronoi diagram(WAY 6) uses polygons to represent area as well to visualize magnitude, except instead of rectangles or wedges. The Voronoi diagram is more flexible over some of the problems when restricted to rectangles to represent areas. One example is:
If you want to focus on a single data point and need to show every individual count within a data point, then consider using the Everything(WAY 7) . It takes up a lot of space, but sometimes puts things in better perspective, like in this way:
The Nightingale rose graph – or the polar area diagram(WAY 8), coined after its creator, Florence Nightingale, is like a combination of the stacked bar and pie chart. The length of radius is used to indicate one thing, usually a count, and polar area represents a portion of the whole. I like to tell you more on the Nightingale rose graph in some future post, and looks like this:
I hope I have not drawn you too deep technically into this blog post, but I wish you can respond and talk about these things in your life and work, by leaving your comments.
