Best method to analyse survey results with multiple choice of answers I have designed a survey with multiple choice answers. Each question contains same set of answers 


*

*Strongly agree 

*Agree 

*Disagree 

*Strongly disagree

*Don't know


There are 25 questions and questions are grouped into 5 areas. I need to analyze each area.
What is the best approach to analyze the survey results which I collected from a number of people? Is it a good method to calculate the mean response from each area as I need area-wise analysis of questions? Can any one suggest a best option? I am not a statistician
Thanks in advance
 A: I upvoted simply because the downvote was uncalled-for.  
To answer the question:


*

*Nobody can tell you how to analyze anything unless they have some idea of why you want to analyze it.  That said:

*If you just want to display the data, make a bunch of bar charts.  People can see who put what, and how frequently.  Done.

*Do you want to say how two variables are related?  Maybe that agreeing with one question predicts disagreeing with another?  That is regression or one of its flavors.  Do some basic reading.  The simple stuff isn't really that hard, and excel can do a lot of really basic stuff.

*Do you want to group people into clusters?  People who think alike?  That is a lot harder.  PCA, kmeans, etc.  Let us know what your goals are and we'll try to point you in the right direction.

A: Following up on points 3 and 4 by ACD:
I would suggest that you take a look at Latent Class Analysis which handles properly your categorial data, assuming that your grouping of questions represents different latent constructs. In case you are interested in connections (e.g. correlated error terms) or even causal links between your "groups", there are also Latent Class Models which are kind of a mix between Structural Equation Models and Latent Class Analysis.
