# Whether to use Spearman's rho or multiple regression to examine relationship between two Likert scales?

I am doing my thesis and have absolutely no previous experience in statistics.

I have constructed several Likert scales by forming composites scores each based on 4-6 items which tests the level of agreement of my respondents.

Specifically, I have created two scales 'purchase behaviour' and 'website appeal'. I want to see whether 'website appeal' is correlated with 'purchase behavior'.

Now that I am doing my analysis, I am confused as to whether I should use Spearman rho or multiple regression. The Spearman correlation and multiple regression have different p-values, so much so that one states that I need to reject my hypothesis and another accept.

So in this case should I use Spearman's rho or multiple regression?

Is there a theoretical rule that I must use, say, multiple regression because I am testing 4-6 items on the likert, although I have grouped them together and intend to 'view' them as two single variables.

Thanks, Jeromy. The article by Gelman and Stern (2006) is really interesting! Being the non-statistician me and trying to get on with my MBA thesis, I would be very tempted to find an analysis which gives me a simple method to analyse my data and ultimately, test my hypotheses. I know this shouldn't be the way, but stats aren't exactly fun nor interesting. I was talking to my supervisor and he suggested using regression when I had planned to use Spearman (cos Likert scale items are ordinal and if I want to test ordinal vs ordinal, I use Spearman - according to my research methods text)

Yes, I am planning to test only two variables (predictors?) at a time, so, Spearman can technically be used. But these two variables (both dependent and independent) are computed as a new variable from the different items I have on the Likert scale (does this make sense?). I am just concerned that my analysis would be deemed incorrect if I used the 'wrong' statistical analysis - or doesn't this matter?