# How can I know a random small subsample has a good performance?

Sorry, if the title is confusing. not native speaker here.

I ran a survey study which had 15 7-point likert scale questions. Each question is ask people to judge how creativity an object in the picture. I received 153 responses in total.

What I try to understand is whether those people who answered the survey did a similar judgement as experts do.

I have 15 experts completed the same survey and compute the mean rating for each picture. For the 153 responses (I call this group as crowd), I also calculated the mean rating for each picture.

Here is the mean rating data of the two groups (E-experts, C-crowd)

E   C
3.36    2.33
1.43    1.53
1.07    1.19
2.43    2.69
2.14    1.92
4.64    4.22
4.71    4.36
4.00    3.24
4.21    3.20
5.07    4.78
4.36    3.41
4.64    5.02
6.14    5.50
5.79    5.73
6.00    5.95


my first question about the data is whether the two group did the judgment similar? could I do a simple t-test comparing the mean rating of 15 questions and tell the result?

second, since I do the survey for an application design. In the real system, for each picture , I could expect only 15-20 people come to rate it. So I want to know if 153 responses I collected now say they do similar judgements as those experts(n=15) do, whether I could say random 15 people could also do similar judgement?

How can I know a small sample (a subsample) has a similar performance as a big sample has?

one way I think about is to random subsample 15 people from the 153 responses for 10000times, and use the mean rating to be compared with the mean rating of 153 responses. but I'm not sure whether it is a right way to do it.