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Misleading Graphs and Statistics. “Lies, damned lies, and statistics”  Statistics are commonly used to make a point or back-up one’s position 82.5% of.

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Presentation on theme: "Misleading Graphs and Statistics. “Lies, damned lies, and statistics”  Statistics are commonly used to make a point or back-up one’s position 82.5% of."— Presentation transcript:

1 Misleading Graphs and Statistics

2 “Lies, damned lies, and statistics”  Statistics are commonly used to make a point or back-up one’s position 82.5% of all statistics are made up on the spot.

3 The “Average” Person…  Be wary when politicians use the word “average” when making a point.  When the data are likely to be skewed, you should ask: What kind of average did you use?

4 U.S. Income Distribution Source: 11/8/2007 3:07 PM

5 Manipulating Information  By adjusting the type and scale of graphical displays, they can be used to highlight desirable information or (hide undesirable information). While this is not always bad, it should make you aware of the danger of taking graphical displays at face value.  You should also be wary of the results of surveys, especially when you do not know how the survey was collected / administered / worded.

6 Sampling Issues  Those being polled are not always honest! (Imagine a cop surveying teens on drug use) E.g. “The Bradley Effect” -- an issue related to race discrimination; getting a lot of airtime lately re: the election. (There’s a “Reverse Bradley Effect” too!)  Is the sample biased (intentionally or not)? (Political polls of likely voters under-represent cell-phone users)

7 Ways to Manipulate Graphs  Scale and Axis Manipulation (Line, Bar Graphs)  Cropping to focus on desirable information (Esp. w/ Line Graphs)  Three dimensional effects (e.g., perspective & “volume”)  Pictorial Embellishments (e.g., “cartoon” effects, leading the readers’ eye)

8 Starting Point  Mayor Marcus is running for a second term against a challenger. Which graph should he send to the local journalist who is reporting on crime rates?

9 What’s wrong with this picture?

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21 Types of Sampling Bias  A bias is a flaw in the sampling procedure that makes it more likely that the sample will not be representative of the population. Faulty sampling (Sample is not representative) Leading questions (Questions are worded so as to influence the answers) Faulty interviewing (Failure to interview the entire sample, misreading questions, misinterpreting what was said) Lack of understanding or knowledge (Person being interviewed does not understand or does not have the information needed) False answers (Person being interviewed intentionally gives incorrect information)

22 What’s wrong with this sample?  A uniformed police officer surveys teens at a local high school athletics competition about drug activity in the school.  Compare the following survey questions: “Should the university use trees harvested during construction to build furniture in the new chemistry building?” “Should the university cut down trees in the construction zone to use as furniture in the new chemistry building?”

23 What’s wrong with this sample?  Third grade students are asked, “How nutritious are your evening meals?”  Literary Digest magazine asked its subscribers to RSVP saying whether they would vote for Landon or for Roosevelt in the 1936 presidential election.


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