Co-authorship is actually really important in some fields. Firstly, it means that everyone is fairly credited. Secondly, it can actually be a bit of a selling point if you have co-authored with prof big head.

On the other hand, gift authorship is wrong.
To be a co-author generally you should have contributed to the paper writing (this can be a 'its fine) and approved the final version. In addition, you should have had some involvement in the design / concept of the study, data collection, or data analysis.

Of course, author order is another issue of controversy. First, second, third and last are generally most important.

Hi virtualwriter,

I suspect most people will be quite petty and expect a proofreader to be able to use punctuation.

Ta muchly though.

I am a bit confused by your description.... Did any of these people receive an intervention, or is this simply one group where some did well and some did not?

You need to be a very careful with what you are planning to do.... It sounds like a fishing trip to me. What is your hypothesis? Did you have a pre-defined statistical plan?

I think you are going to need a very strong argument for reporting means and using a t-test.

To me, that paper suggests that there is little point using a t-test if a mann-whitney has equivalent power.

I don't know how to interpret 3.5- at a rough guess, it means slightly less important than very important.
Also, is your data actually normally distributed?

Think you need to justify use of a t-test, as your data appears to be ordinal, rather than continuous.
In that context, mean and confidence intervals are meaningless.