Message expanded. Message read Variability and clarity
posted by GENNIFER PETERS , May 26, 2016, 4:49 PM
According to Tokunaga, The word variability is typically related to words such as differences, dispersion, or changes. In a statistical sense, variability refers to the amount of spread or scatter of scores in a distribution (2016). Depending on the type of graph that you're using you can have a high low where your data is plotted at the high-end middle and the low-end. The variability in this case would be the span of all the data plots. There's also a chart it looks like a "T" or cross. In this type of graph the data plus maybe more spread out. The disbursement of the data plot is the variability for that research. The researcher has to look at the range of the data in order to see if the variability is higher low. In my experience I have found that connecting the dots and some sort of way helps the reader to better understand the graph. Unless, there are a high number of data points where and easily identifiable cluster is made some charts can be difficult to read and understand. Having key identifiers in your chart provide additional clarity and take away any type of guessing.
Reference
Tokunaga, H. (2016). Fundamental statistics for the social and behavioral sciences. Sage publishing.