“The examples in this chapter have demonstrated how the apparently simple task of calculating and communicating proportions can become a complex matter.”
[The Art of Statistics, David Spiegelhalter]
Thanks to you, the number of followers increases by 22% in November! When you see this sentence, you may think that this emerging blog is growing rapidly and there are some reasons for this success. If I wrote “4 people start to follow my blog in November”, you might have a different feeling. But both are true: my blog has 18 followers in October and now 22. Different representations in statistics can change the impact of observations, we called this positive (or negative) framing. There are many examples of positive or negative framing. For example, pharmaceutical companies want to say that a new medicine has a 95% survival rate rather than a 5% mortality rate (positive framing). Investigative journalists want to say that 3,000,000 people are suspected of tax evasion every year rather than 1% of people (negative framing). This framing also appears in the graph. Assume that we need to draw a bar chart with two bars whose values are 95 and 98, respectively. If we draw a bar chart from 0 to 100, the two bars look similar. However, if we draw a bar chart from 90 to 100, we see totally different bars on the graph.
How can we escape from this framing? Information providers should provide alternative data representations (different graphs, law data, tables) so that we can get a balanced view of the data by examining raw data. Also, we always should be skeptical when we see data. First, we should check who (and why) published statistical data; data do not lie, only presenters may lie. However, this argument does not refer to that statistics are totally crafty tricks. Statistics is still powerful to understand, analyze, and visualize data effectively. Moreover, in the age of Big Data, statistical knowledge is fast becoming the main tool to deal with big data correctly. That is, statistics are a double-edged sword; the power of statistics depends on us.