Where did you get the value for "gas consumption"? Is it for household gas usage and not just the cylinders? Then the gas usage would automatically increase during the winter time for heating but cylinder usage might decrease because people usually cook outdoor when the weather is good. Also, is this a nationwide values?

"SD" <saurabhkdas@gmail.com> wrote in message news:726074a7-7543-49a7-8bd0-525207942e0a@o9g2000vbj.googlegroups.com... > Hello everyone, > > I am not a stats guy, however I have a project I need to finish. The > null hypothesis is increase in sales of cooking gas cylinders means > increase consumption/usage of cooking gas . > > I did a correlation between two variables "cooking gas cylinders" and > gas consumption. I have monthly data points from 2006 to 2009 Sep. > And I am getting negative correlation. what should be my next > approach , because in my mind I know that atleast it should not be > negatively correlated. Again 40 odd data points is too less to do this > kind of exercise. Any ideas on how go about this, and may be sales of > gas cylinders may not be the real cause of increase of usage of gas, > but certainly not negatively correlated. Just to add, there are 3 > types of gas cylinders, the ones made in 2006 had a different > technology, while the ones made in 2009 are of different technology, I > did do an overall sales vs overall gas usage , and again new > technology gas sales vs gas usage from new technology cylinders, again > negative correlation. > > Now suppose people are buying 2 cylinder, or tri cylinder , that does > not mean they are going to use all of them together, So I tried to > factor in a lag, of 1 to 6 months, again negative correlation. > > dataset looked like > > months cylindersales gas_usage_no_lag lag1 lag2 lag3 > jan06 10 45litres > - - - > feb06 20 75 litres 45litres > - - > mar06 15 67 litres 75 > litres 45litres - > > etc > > Just want to know if my approach is correct and any quick help would > be greatly appreciated. > > thanks in advance > SD