Describe some of the different ways researchers can used Descriptive Statistics to deceive I604-6-2

Figures don’t lie but liars figure!

Misleading Descriptive Statistics include:

Using Average to Mislead
The experimenter may include at least one usually high or low score in test results to distort the average calculated with the objective of misleading those reading the test result.

The Semi-Attached Figure:

From the slides, "If you can't prove, demonstrate something else and pretend that they are the same thing. In the daze that follows the collision of statistics with the human mind, hardly anybody will notice the difference. The semi­ attached figure is a device guaranteed to stand you in good stand."

This type of testing with rather slanted results is reminiscent of the testing that was done years ago with rats and soda containing artificial sweeteners. Yes the poor rats were adversely affected by the sweetener however they would have drowned before they could drink the amount of soda required to contain the corresponding amount of artificial sweetener .

Misleading Graphs:

Graphs can be presented in such a way to suggest misleading results. The example presented in the slides dealing with weight loss would be very deceptive if used in a commercial. Here the results were visually exaggerated by starting the vertical axis at ten pounds rather than zero.
In the lead up to the November election there many graphs produced showing which commercials had greater impact on a group of likely voters, etc.

Perhaps there should have been a greater predictor of how self-identified Born Again Christians would vote. As I understand, more than six million BAC did not vote for “Christian valves.”