Page 36 - Intermediate Statistics for Dummies

05_045206 ch01.qxd 2/1/07 9:41 AM Page 15
Chapter 1: Beyond Number Crunching: The Art and Science of Data Analysis
to just point and click to do as many analyses as they want, without any warn-
ing about what statisticians call the overall error rate (that is, the probability
of making an error due to chance during any step of the entire analysis, not
just the probability of making an error due to chance on any single analysis).
No (data) fishing allowed
Redoing analyses in different ways to try to get the results you want is called
data fishing in the statistics business, and folks in the stat biz consider it to
be a major no-no (however, people unfortunately do it all too often in the
name of research).
For example, Ellen Go-getter is convinced that dissolving sugar in the water
helps cut flowers last longer. She performs an experiment to prove her
hypothesis. She cuts two dozen roses and puts one rose in each vase. She
fills each vase with 3 cups of water, but in 12 of the vases she adds 1 table-
spoon of sugar (the other 12 vases constitute the control group, meaning that 15
Ellen doesn’t apply any new treatment to them to show what happens if she
adds nothing). In the next sections, you follow Ellen through her experiment,
keeping an eye on the statistical analyses that pop up along the way.
Examining Ellen’s data
Ellen counts how many days the flowers still look nice and uses the same cri-
teria for each flower. After ten days, all the flowers have withered to the point
where they need to be thrown away, so the experiment is over. You can see
Ellen’s data in Table 1-1.
Table 1-1 Ellen’s Data: Days Roses Lasted in Sugar Water
versus Regular Water (Control Group)
Observation Days Lasted: Water Only Days Lasted: Sugar Water
1 3 5
2 3 5
3 4 5
4 4 4
5 4 4
6 4 4
7 3 3
(continued)