I have data of an entire population (N=27). I would like to find out which variables (of many) have the greatest effect on one certain dependent variable, and how much of its variance can they explain. The possible independent variables could be correlating as well (some of them certainly do). They are all scale measured.
What do you think would be the best method to use and what should I pay attention to?
I'm limited to SPSS, and rather sketchy statistical knowledge. I have been trying to get something with linear regression but I fail to achieve anything interpretable, and it crossed my mind that I might need something entirely different since this is not a sample.
Thanks in advance!
EDIT: For this question this might not be important, but: I have all the variables 5 times for 5 separate years. Later on I am planning on examining how the effect of a variable changes over time.
EDIT nr.2: After the first replies it seems the best to detail the database I have: The 27 cases are 27 European countries, and the dependent variable is the percentage of their population that participated in demonstrations in that year. I also have lots of possible independent variables like gdp, unemployment, happiness, etc. I have all these values for 5 separate years. And basically I'm trying to find something that I can write about in my thesis, like "gdp is the biggest factor and its twice as big as happiness blabla ...in these countries". The reason why I'm saying its the entire population, because I am not planning on drawing general conclusions. I wouldn't be able to do that anyway as the countries aren't even representative for Europe.