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2.4 Graphical Misrepresentations of Data Objective: By the end of this section, I will be able to… 1) Understand what can make a graph misleading, confusing, or deceptive.
1) Inappropriate Choice of Statistic Survey: Find the number of robberies in Manhattan, Wilmington, Philadelphia, and Phoenix.
2) Omitting a Zero on the Scale
3) Manipulating the Scales
4) Using 2D for a 1D difference
5) Careless combination of categories
6) Unclear or inaccurate labeling
7) Biased Distortion
Are they the same? The graphs below show the number of people who rode buses from September through February.
CREATE TWO GRAPHS 1)One regular graph 2)One misleading graph 3)Label both graphs clearly!