1. Section 2-5
“Bad Graphs”

2. Learning Targets
Some graphs are bad in the sense that they contain errors.
Some are bad because they are technically correct, but misleading.
It is important to develop the ability to recognize bad graphs and identify exactly how they are misleading.

3. Are these graphs the same?
Case One
Scaling Errors!
Non-Zero Axis
Are these graphs the same?

4. (Changing Graphing Scales)
Nonzero Axis
(Changing Graphing Scales)
-misleading because one or both of the axes begin at some value other than zero, so that differences are exaggerated.

5. Changing Graph Scales
(Average Home Prices)
Example A:

6. Changing Graph Scales (Graduation Rates) Example B:
Year
1999
2000
2001
2002
2003
Number of Graduates
140
180
200
210
160
Left makes it seem as if students are dropping out of school left ad right. This can make a lot of people concerned. When in reality, there is just a slight decrease…
Here they are only looking at the tree when they should try to see the whole forest!
Makes as seem though half did not graduate when really it’s a fourth.

7. Is anything misleading in this graph?
No Labels!
We have no idea what the graph may be talking about!
No Consistancy!
Is anything misleading in this graph?

8. 1 2 3

9. 1 2 3

10. Is anything misleading in this graph?
Case 2
(Pictographs)
Is anything misleading in this graph?

11. Pictographs
are drawings of objects. Three-dimensional objects - money bags, stacks of coins, army tanks (for army expenditures), people (for population sizes), barrels (for oil production), and houses (for home construction) are commonly used to depict data.

12. These drawings can create false impressions that distort the data.
Pictographs using areas and volumes can therefore be very misleading.
Example C: If you double each side of a square, the area does not merely double; it increases by a factor of four;
(Similarly, if you double each side of a cube, the volume does not merely double; it increases by a factor of eight.)

13. Example D:

14. Annual Incomes of Groups with Different Education Levels
Example E:
Bars have same width, too busy, too difficult to understand.

15. Annual Incomes of Groups with Different Education Levels
Example F:
Misleading. Depicts one-dimensional data with three-dimensional boxes. Last box is 64 times as large as first box, but income is only 4 times as large.

16. Annual Incomes of Groups with Different Education Levels
Example G:
Fair, objective, unencumbered by distracting features.

17. Case 3: Is anything wrong with this graph?

18. Are these graphs the same?
Case Three
Pictographs!
Fancy, but might skew the perception…
Are these graphs the same?

19. Researchers asked people to identify their 3 favorite pies – adds up to 300%

20. Misleading Statistical Statements:
1.) You are more likely to die on the toilet than to be eaten by a shark.
2.) The FBI's Uniform Crime Reports (UCR) shows arrests of juvenile females for assaults and violent crime from 1980 through 2003 rose from 20 percent to more than 30 percent of the total.

21. 2.) Continued:
This is a perfect example of needing more information. The reality was that actual girl violence wasn’t shown to go up but the prosecution of girls did. A girl is more likely to get arrested for the same type of fight in 2003 than in 1980.

22. What is wrong with the following line graph?
Apply it!
What is wrong with the following line graph?
What is this
graph comparing???
Do we know how
to count???

23. Supposed to doubles, but the volume actually increased by 8….
Apply it!
Doug’s Dog Food Company wanted to impress the public with the magnitude of the company’s growth. Sales of Doug’s Dog Food had doubled from 2002 to 2003, so the company displayed the following graph, in which the radius of the base and the height of the 2003 can are double those of the 2002 can.
What does the graph really show with respect to the growth of the company?
Pictographs!
Supposed to doubles, but the volume actually increased by 8….
Supposed to doubles, but the volume actually increased by 8….

24. Misleading highlighting...
Apply it!
What’s wrong with the following graph?
Scale…
Misleading highlighting...
Why are they all
not on the x-axis?