Difference between revisions of "Correlation"
Jump to navigation
Jump to search
(statistical relation between two or more variables such that systematic changes in the value of one variable are accompanied by systematic changes in the other) |
(A correlation between two variables does not always mean that one variable has caused a change in the other) |
||
| Line 6: | Line 6: | ||
==Correlation and causation== | ==Correlation and causation== | ||
| − | + | A [[correlation]] between two variables does not always mean that one variable has caused a change in the other. It is a [[logical fallacy]] to assume that correlation implies causation. | |
The following is a flawed argument: | The following is a flawed argument: | ||
Revision as of 20:19, October 13, 2007
Correlation is defined by dict.org as:
- a statistical relation between two or more variables such that systematic changes in the value of one variable are accompanied by systematic changes in the other [1]
In other words, if you are studying two
Correlation and causation
A correlation between two variables does not always mean that one variable has caused a change in the other. It is a logical fallacy to assume that correlation implies causation.
The following is a flawed argument:
- Event A occurs in concurrence with Event B
- Therefore, Event A causes Event B
This is flawed because:
- There may be a confounding factor causing A and B
- B may cause A
- The relationship may be a complete coincidence
Examples
- As sales of ice cream rise, so do reports of shark attacks
- High sales of ice cream cause shark attacks
Flaw: Shark attacks and ice cream sales follow a seasonal pattern. Both rise in the summer months. The seasons are a confounding variable.
- Since the construction of a stadium began in Alaska, the value of your home in Texas has risen
- Stadium construction in Alaska causes higher home values in Texas
Flaw: This is a coincidence between unrelated variables.