I have a survey analysis data which has responses regarding Consumer Satisfaction (on a scale of 1 to 5)and I am trying to fit a linear regression model to it. As per my understanding, the basic assumption for linear regression is that the independent variables must not show significant correlation. In my case however, since the responses are filled by people (homo-sapiens), the responses are showing correlations within a category and across categories (Food, Facility etc). Is this a cause for concern? Can I still go ahead and apply linear regression or should I combine the correlated responses? Also if I were to combine responses, how should I go about it? Thanks in advance!

I have a survey analysis data which has responses regarding Consumer Satisfaction (on a scale of 1 to 5)and I am trying to fit a linear regression model to it. As per my understanding, the basic assumption for linear regression is that the independent variables must not show significant correlation. In my case however, since the responses are filled by people (homo-sapiens), the responses are showing correlations within a category and across categories (Food, Facility etc). Is this a cause for concern? Can I still go ahead and apply linear regression or should I combine the correlated responses? Also if I were to combine responses, how should I go about it? I have had to make changes to the responses (independent and dependent variables) based on a scorecard:

Excellent 100 Very good 90 Good 75 Fair 25 Poor 0

I have two approaches in mind:

1. I can run a linear regression based on the scorecard
2. I keep the responses to my dependent variable as "Excellent, Very good, Good, Fair, Poor", change the responses to the independent variables according to the scorecard and apply an Ordinal Logistic Regression

Can you guys help me pick the most proper approach.

Thanks!