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Information Representation and Visual HCI

             To achieve graphical excellence, statistical data should communicate complex ideas with clarity, precision and efficiency. The above diagram does neither and is a bad example of information representation. There are a number of flaws that we will discuss in further detail.
             Firstly the most obvious flaws the viewer will instantly see is the large title, which is the province of Manitoba. The graph should draw the viewer's attention to the substance and not to something else. It is a nice picture that is eye catching due to its size but is not appropriate or relevant and shouldn't take up the majority of the graph. An ill-specified or puny amount of data cannot e rescued by a graphic, no matter how fancy. .
             A large amount of data ink had been wasted on this simple representation of data. Data ink is the non-erasable core of the graphic, the actual data that is being represented. A simple line graph would be more appropriate however too much colour and space has been wasted on irrelevant graphics.
             Another fundamental error is that the graph has not been given any units on the axis. It is impossible to determine the rate at which the inflation or wages is falling. No information has been given even in the text that the fall is dramatic or slight. The viewer's perception of the graph is simply that wages have fallen due to inflation. The viewer's perception is further baffled as the two graphs are displaced from each other and make it more difficult for the viewer to compare the slopes of lines. This brings me to the lie factor.
             The lie factor calculates the misrepresentation of data. Without knowing the units it is difficult to determine the exact lie factor, but using inconjunction the graph below we can detimine the lie factor. A number higher than 1 means that the data has been distorted and will involve overstating, his is not uncommon. Here is a reworked graph to show the actual rate of decline.

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