Tuesday, October 12, 2010

A Short Introduction to Correlations

Via Sociological Images, a great graph (any clear, easy to read graph is pretty great) and interesting analysis of the *positive correlation between income and SAT scores, from data published by The College Board. There's a pretty strong relationship implied here - one that raises questions about the ongoing reproduction of class inequality and the hidden bias of standardized tests (as discussed briefly in relation to IQ tests - see Stephen Jay Gould).

©2010 Sociological Images

* Positive Correlation: Defined by Timothy C. Urdan as: "A characteristic of a correlation; when the scores on the two correlated variables move in the same direction, on average. As the scores on one variable rise, scores on the other variable rise, and vice versa." (For more, see Urdan, T.C. (2005) Statistics in Plain English (2nd edition). Lawrence Erlbaum Associates, Inc.)

Note: Positive/negative correlations are found through "Correlational Analysis," which measures the strength of an association between two variables. Values range from +1.00 to –1.00. 

Rule of Thumb: Correlation should NEVER be confused with causation = they are very different things, and involve a very different set of calculations and often different research designs (methods, analysis, control groups, etc.). Causation causes correlation, but it is not necessarily the other way around. It is much easier to establish correlation than causation. And it is also very easy to confuse or inflate the significance of correlation - as seen in the media effects debates discussed in this week's Kline reading.

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