Concerning the two texts, it is interesting how deceptive figures can be when handling objective data and statistics. Although the two texts point out that figures should be made to elimitae message reversal and message exaggeration, some points of contention came to mind as to seeing these fake statistics. The first being that what seems like exaggeration is in actuality the true message. Sometimes statistics are made on the fly or on a whim, especially in the realm of sports, and the need to pooint out outliers is crucial to the audeince. For instance, a statistc that creates an average of 75% on a chart, needs to “embellish” viewing a 60% on the same chart - if you regularly have the axis out of a 100 then you would not necessarily see the outlier. The second point is who is the fault on when the message is viewed wrongly despite being given all the data. If the graph was presented without features, then the fault would objectively be on the graph maker, but if having all the labels and features, the person still makes an exaggeration then it is on the fault of the audience, and how short their attention span is. Unless what the writers are advising is to to present information as if the audience has no deductive reasoning skills, then that is another area of conversation.