Correlation, Term Paper Example

When conclusions are made based on statistical correlations, there are a number of cautionary points that should be observed: First, correlation is not equal to causation.  That is, although two variables might have a positive (or negative) correlation,  the correlation is not informative regarding whether one variable causes another (Cohen, 2001).  Second, the correlation is usually tied to a particular sample data set that may or may not be represenative of the “true” relationship between the variables in the population.  An example of spurious causation is that many medical studie have found a robust correlation between alcohol and lung cancer.  After investigation, however, medical reserachers found that people who drink also like to smoke- the correlation coeffiecient was representative of smoking’s contribution to lung cancer, not drinking.

A “perfect” correlation coefficient (of 1.00) means that the two variables being examined are perfectly correlated the change in one is a multiple of the change in the other (Howith & Cramer, 2005).  The sign of the correlation coefficient is related to the putative relationships between variables: A positive correlation coefficient means that an increase in one variable leads to an increase in another variable; a negative correlation coefficient indicates a negative effect in that an increase in one variable leads to a decrease in another variable. An example of a strong positive correlation in my life is between time spent on homework and test performance: more time spent on studying (to a certain point) results in higher grades.  An example of a negative correlation in my life is time spent exercising and weight: an increase in the time spent exercising is correlated with a decrease in weight.  A weak correlation is found in the relationship between consumption of soda pop and grades: Regardless of drinking more or less soda pop, grades roughly stay the same.

References

Cohen, B. (2001).  Explaining Psychological Statistics.  New York: Wiley.

Howith, D. & Cramer, D. (2005).  An Introduction to Statistics in Psychology.  New York: Prentice Hall.