A note on Cronbach's alpha
[http://www.bmj.com/cgi/content/full/314/7080/572 Bland JM, Altman DG (1997) Statistics notes: Cronbach's alpha. BMJ 314 572]
The above article suggests rules of thumb for Cronbach's $$\alpha$$ and examples of its use. In particular a value of 0.70 is deemed to be 'satisfactory'.
Cronbach's alpha is defined as
$$\frac{k}{k-1} (1 - \frac{\mbox{Sum of k item variances}}{\mbox{Variance of total scores}} )$$
In particular Bland and Altman (1997) note that
Cronbach's alpha has a direct interpretation. The items in our test are only some of the many possible items which could be used to make the total score. If we were to choose two random samples of k of these possible items, we would have two different scores each made up of k items. The expected correlation between these scores is $$\alpha$$.